Statistical analysis method and system for metal material inclusions

Abstract

The invention provides a statistical analysis method and system for metal material inclusions, and relates to the field of statistics of non-metallic inclusions in steel. The method comprises the following steps: preparing a to-be-tested sample and putting the sample into a testing instrument; setting an inclusion statistical analysis program according to analysis requirements; dividing the to-be-detected area into a plurality of view fields, respectively acquiring view field images of the to-be-detected sample in each view field according to an acquisition sequence, and identifying score deduction factors existing in each view field image; according to a preset rule, calculating the score of each field of view to judge the effectiveness of the field of view; and carrying out inclusion energy spectrum analysis on the field of view which is judged to be effective, and counting the inclusions in a plurality of effective fields of view. According to the method, the second phase counted in the view field is evaluated, when the score deduction factor exists in the second phase, the score of the view field is reduced, then the view field effectiveness is judged, only the effective view field is further analyzed and processed, and the recognition efficiency is improved while the test accuracy is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of statistics of non-metallic inclusions in steel, and particularly relates to a method and system for statistical analysis of inclusions in metal materials. Background Art

[0002] Inclusions in steel refer to the general term for various non-metallic particle substances entrained in steel, including endogenous inclusions and exogenous inclusions, mainly composed of deoxidation products in steelmaking, precipitates formed by physical and chemical reactions during steel solidification, inclusions formed after steel slag is involved in molten steel, etc. The types include oxides, sulfides, silicates, nitrides, etc. The existence of inclusions will destroy the continuity of the steel matrix, reduce mechanical properties, affect processing performance, reduce corrosion resistance and affect service life and other problems. Therefore, it is necessary to strictly control the quantity and morphology of inclusions during steelmaking and steel processing.

[0003] The level of inclusions in steel can be evaluated by automatically counting inclusions using a scanning electron microscope / energy spectrometer. This method scans each field of view on the sample surface using a scanning electron microscope, performs energy spectrum composition analysis after identifying inclusion particles, and finally obtains information such as the position, size and composition of inclusions on the entire sample. However, during sample detection, due to differences in the polishing effect at different positions of the sample, there is usually a situation where the polishing effect at the edge is poor and the polishing effect at the center is good. When there are defects such as cracks in the set detection area or beyond the sample, the area outside the sample will be detected, which not only reduces the recognition accuracy and detection efficiency, but also interferes with the detection results. Therefore, on the premise of ensuring the statistical accuracy of inclusions, improving the statistical efficiency of inclusion detection is of great significance for optimizing the steelmaking process. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for statistical analysis of inclusions in metal materials, which exclude some fields of view that affect the statistical accuracy and high time consumption of inclusions by evaluating the collected fields of view, improve the statistical efficiency and reduce misjudgment.

[0005] To achieve the above object, the present invention proposes the following technical solutions:

[0006] In the first aspect, a method for statistical analysis of inclusions in metal materials is proposed, including the following steps:

[0007] Prepare a test sample containing the test specimen and reference material, and place it in a test instrument pre-installed with an inclusion analysis system; wherein, the test specimen is a polished metal block;

[0008] According to the analysis requirements, set the inclusion statistical analysis program, including determining the rolling direction and photometric parameters of the test specimen, the working parameters of the test instrument and the detection area to be detected;

[0009] Divide the area to be detected into several fields of view, obtain the field-of-view images of the sample to be tested in each of the fields of view in the acquisition order, and identify the deduction factors existing in each of the field-of-view images; wherein, the deduction factors include the aspect ratio of the second phase, the quantity of the second phase, the direction of the second phase, and the invalid detection area.

[0010] According to the preset rules, calculate and judge the magnitude relationship between the score of each field of view and the preset threshold. When the score is not less than the preset threshold, determine that the field of view is valid; wherein, the preset rules are deduction rules formulated based on several deduction factors that affect the accurate statistics of inclusions within the field of view.

[0011] Perform energy spectrum analysis on the inclusions in the fields of view determined to be valid, and count the inclusions in several valid fields of view to complete the statistical analysis of the inclusions in the area to be detected.

[0012] Further, the process of calculating the score of any field of view according to the preset rules is as follows:

[0013] If it is determined that the deduction factors existing in the field-of-view image include the aspect ratio of the second phase, then when the aspect ratio of the second phase is greater than the first set value, deduct points according to the exceeding ratio of the aspect ratio, otherwise do not deduct points; wherein, the value range of the first set value is 1 to 50, and the deduction range is 0 to 30.

[0014] If it is determined that the deduction factors existing in the field-of-view image include the quantity of the second phase, then when the quantity of the second phase is greater than the second set value, deduct points according to the exceeding ratio of the quantity, otherwise do not deduct points; wherein, the second set value is not less than 10, and the deduction range is 0 to 30.

[0015] If it is determined that the deduction factors existing in the field-of-view image include the direction of the second phase, then when the deviation angle of the direction of the second phase from the rolling direction is greater than the third set value, deduct points according to the exceeding ratio of the deviation angle, otherwise do not deduct points; wherein, the value range of the third set value is 10° to 90°, and the deduction range is 0 to 50.

[0016] If it is determined that the deduction factors existing in the field-of-view image include the invalid detection area, then when the proportion of the area of the second phase in the field of view to the area of a single field of view is greater than the fourth set value, deduct points according to the exceeding ratio of the proportion, otherwise do not deduct points; wherein, the value range of the fourth set value is 1% to 30%, and the deduction range is 0 to 50.

[0017] Calculate the difference between the total ideal score and the deduction items corresponding to each of the deduction factors to obtain the score of the field of view.

[0018] Further, when there is no rolling direction for the sample to be tested, the value range of the first set value is 1 to 2.

[0019] Further, the aspect ratio of the second phase for judging the deviation angle is not less than 2.

[0020] Further, when there is no rolling direction for the sample to be tested, the third set value is 90°.

[0021] Further, the several visual fields divided by the area to be detected are equal.

[0022] Further, the value range of the preset threshold is 60 to 100.

[0023] Further, the photometric parameters for determining the sample to be tested are as follows: setting the gray value of the matrix to be 170 - 220, setting the gray value of the reference material to be 30 - 70, and determining the working parameters of the testing instrument by setting the brightness and contrast of the testing instrument according to the gray values of the matrix and the reference material.

[0024] In a second aspect, a statistical analysis system for inclusions in metal materials is proposed, including:

[0025] A sample preparation module, used to prepare a sample to be tested containing the sample to be tested and the reference material, and place it in a testing instrument, in which an inclusion analysis system is pre - installed; among them, the sample to be tested is a polished metal block;

[0026] A program setting module, used to set an inclusion statistical analysis program according to the analysis requirements, including determining the rolling direction and photometric parameters of the sample to be tested, the working parameters of the testing instrument, and the area to be detected;

[0027] An acquisition and recognition module, used to divide the area to be detected into several visual fields, sequentially acquire the visual field images of the sample to be tested in each visual field according to the acquisition order, and identify the deduction factors existing in each visual field image; among them, the deduction factors include the aspect ratio of the second phase, the number of the second phase, the direction of the second phase, and the invalid detection area;

[0028] A calculation and judgment module, used to calculate and judge the size relationship between the score of each visual field and the preset threshold according to the preset rules, and determine that the visual field is valid when the score is not less than the preset threshold; among them, the preset rules are deduction rules formulated according to several deduction factors affecting the accurate statistics of inclusions in the visual field;

[0029] An analysis and statistics module, used to perform energy spectrum analysis on the inclusions in the visual fields determined to be valid, count the inclusions in several valid visual fields, and complete the statistical analysis of the inclusions in the area to be detected.

[0030] Further, the execution unit of the calculation and judgment module for calculating the score of any one of the fields of view according to a preset rule includes:

[0031] A first judgment unit, configured to judge that if the aspect ratio of the second phase is included in the deduction factors existing in the field of view image, when the aspect ratio of the second phase is greater than a first set value, deduction is performed according to the exceeding ratio of the aspect ratio, otherwise no deduction is performed; wherein, the value range of the first set value is 1 to 50, and the deduction range is 0 to 30;

[0032] A second judgment unit, configured to judge that if the number of the second phases is included in the deduction factors existing in the field of view image, when the number of the second phases is greater than a second set value, deduction is performed according to the exceeding ratio of the number, otherwise no deduction is performed; wherein, the second set value is not less than 10, and the deduction range is 0 to 30;

[0033] A third judgment unit, configured to judge that if the direction of the second phase is included in the deduction factors existing in the field of view image, when the deviation angle between the direction of the second phase and the rolling direction is greater than a third set value, deduction is performed according to the exceeding ratio of the deviation angle, otherwise no deduction is performed; wherein, the value range of the third set value is 10° to 90°, and the deduction range is 0 to 50;

[0034] A fourth judgment unit, configured to judge that if an invalid detection area is included in the deduction factors existing in the field of view image, when the ratio of the area sum of the second phases in the field of view to the area of a single field of view is greater than a fourth set value, deduction is performed according to the exceeding ratio of the ratio, otherwise no deduction is performed; wherein, the value range of the fourth set value is 1% to 30%, and the deduction range is 0 to 50;

[0035] A calculation unit, configured to calculate the difference between the total ideal score and the deduction items corresponding to each of the deduction factors, and obtain the score of the field of view.

[0036] As can be seen from the above technical solutions, the technical solutions of the present invention have obtained the following beneficial effects:

[0037] The statistical analysis method and system for inclusions in metal materials disclosed by the present invention, the method includes: preparing a test sample to be tested and placing it in a testing instrument; setting an inclusion statistical analysis program according to the analysis requirements; dividing the area to be detected into several fields of view, respectively obtaining the field-of-view images of the test sample in each field of view according to the acquisition sequence, and identifying the deduction factors existing in each field-of-view image; calculating the score of each field of view according to a preset rule to determine the validity of the field of view; performing energy spectrum analysis on the inclusions in the fields of view determined to be valid, and counting the inclusions in several valid fields of view. By evaluating the second phase statistically in the field of view, when there are deduction factors for the second phase, the score of the field of view is reduced, and the validity of the market is determined according to the comparison result between the field-of-view score and a preset threshold. Only the valid fields of view are further analyzed and processed, so as to ensure the accuracy of inclusion statistics while improving the recognition efficiency.

[0038] Aiming at the problems that when analyzing and counting inclusions at present, if the sample preparation effect is poor, it will lead to distortion of inclusion statistical data, extension of time, etc., by identifying the features in the field-of-view image, when there are many abnormal features in the detected field of view, such as non-sample area, foreign objects, holes, polishing materials, etc., skipping the energy spectrum analysis of this field of view and proceeding to the detection of the next field of view, finally achieving the technical effect of improving the accuracy of inclusion recognition, and at the same time improving the efficiency of inclusion analysis.

[0039] It should be understood that all combinations of the foregoing concepts and additional concepts described in more detail below can be regarded as part of the inventive subject matter of the present disclosure as long as such concepts do not contradict each other.

[0040] The foregoing and other aspects, embodiments and features of the teachings of the present invention can be more fully understood from the following description in conjunction with the accompanying drawings. Other additional aspects of the present invention, such as the features and / or beneficial effects of exemplary embodiments, will be apparent in the following description, or will be learned through the practice of specific embodiments according to the teachings of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The drawings are not drawn to scale with respect to actual reference objects. In the drawings, each identical or approximately identical component shown in each figure may be denoted by the same reference numeral. For clarity, not every component is labeled in each figure. Now, embodiments of various aspects of the present invention will be described by way of example and with reference to the drawings, wherein:

[0042] Figure 1 It is a schematic diagram of a field of view normally collected in the prior art for inclusion statistical analysis;

[0043] Figure 2 It is a schematic diagram of a field of view with many scratches in the prior art for inclusion statistical analysis;

[0044] Figure 3Schematic diagram of the field of view when there is a lot of grinding and polishing material in the statistical analysis of inclusions in the prior art;

[0045] Figure 4 Schematic diagram of the field of view when foreign matter invades in the statistical analysis of inclusions in the prior art;

[0046] Figure 5 Schematic diagram of the field of view for identifying invalid detection areas in the statistical analysis of inclusions in the prior art;

[0047] Figure 6 Flow chart of the statistical analysis method for inclusions in metal materials disclosed by the present invention;

[0048] Figure 7 Structure block diagram of the statistical analysis system for inclusions in metal materials disclosed by the present invention. Detailed implementation manners

[0049] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the described embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention. Unless otherwise defined, the technical terms or scientific terms used herein shall have the ordinary meanings understood by those of ordinary skill in the art to which the present invention pertains.

[0050] The "first", "second" and similar terms used in the specification and claims of this patent application of the present invention do not denote any order, quantity or importance, but are only used to distinguish different components. Similarly, unless clearly specified otherwise in the context, the singular forms of "a", "an" or "the" and similar terms do not denote a quantity limitation, but mean that there is at least one. The terms such as "including" or "comprising" mean that the elements or objects appearing before "including" or "comprising" cover the features, wholes, steps, operations, elements and / or components listed after "including" or "comprising", and do not exclude the existence or addition of one or more other features, wholes, steps, operations, elements, components and / or their combinations. The terms such as "up", "down", "left" and "right" are only used to represent relative position relationships. When the absolute position of the object being described changes, the relative position relationship may also change accordingly.

[0051] Based on the fact that the current automatic inclusion statistical program can only perform statistics according to the set program, and these programs cannot accurately identify and judge the fields of view with poor sample preparation effect on the detected surface and invalid detection areas, such as Figure 2-5The fields of view with many scratches, fields of view with more polishing materials, fields of view with foreign matter intrusion, and fields of view with invalid detection areas are shown. Scratches are mostly characterized as elongated second phases extending in the non-rolling direction in the field of view image. These fields of view extend the inclusion statistics time and affect the data statistical accuracy. Therefore, the present invention aims to propose a method and system for statistical analysis of inclusions in metal materials. By evaluating the collected fields of view of the test sample, the fields of view that are not conducive to the statistical accuracy and efficiency of inclusions are excluded, thereby improving the statistical efficiency and statistical accuracy of inclusions.

[0052] Combination Figure 6 As shown, the statistical analysis method for metal material inclusions proposed in the present invention improves statistical efficiency and accuracy by scoring the acquired field of view images to judge the effectiveness of the field of view and decide whether to count the data of the field of view, and includes the following steps:

[0053] Step S102, preparing a sample to be tested including a sample to be tested and a reference material, and placing the sample to be tested in a testing instrument, wherein the testing instrument is pre-installed with an inclusion analysis system; wherein the sample to be tested is a polished metal block, the reference material is pasted on a corner of the metal block, and the testing instrument is a scanning electron microscope or an energy dispersive spectrometer;

[0054] Step S104, according to the analysis requirements, setting the inclusion statistical analysis program, including determining the rolling direction and photometric parameters of the sample to be tested, the working parameters of the test instrument and the area to be tested; specifically, the photometric parameters are mainly grayscale values, and the working parameters of the test instrument are mainly to adjust the brightness and contrast of the test instrument according to the grayscale values; when the method is implemented, the grayscale value of the matrix is ​​set to 170-220, and the grayscale value of the reference material is set to 30-70. In addition, setting the inclusion statistical analysis program also includes setting the area to be tested;

[0055] Step S106, dividing the area to be tested into several fields of view, acquiring field images of the sample to be tested in each field of view in the acquisition order, and identifying the deduction factors existing in each field of view image; wherein the area of ​​each field of view is equal, and the above-mentioned deduction factors include the aspect ratio of the second phase, the number of the second phase, the direction of the second phase and the invalid detection area;

[0056] Step S108, according to the preset rules, calculate and determine the size of the score of each field of view and the preset threshold, and determine that the field of view is valid when the score is not less than the preset threshold; wherein the preset rules are deduction rules formulated according to several deduction factors that affect the accurate statistics of inclusions in the field of view; before the specific test, first determine whether the sample to be tested has a rolling direction, and if so, mark the rolling direction of the sample to be tested, otherwise mark the rolling direction as no;

[0057] Step S110: Perform energy spectrum analysis on the inclusions in the determined valid field of view, count the inclusions in a number of valid fields of view, with the minimum size of the detected inclusions being 2 μm, and complete the statistical analysis of the inclusions in the area to be detected; that is, eliminate the fields of view that affect the statistical accuracy of the inclusions.

[0058] The method for statistical analysis of inclusions in metal materials provided by the present invention evaluates the deduction factors statistically obtained in the field of view to score each field of view. When the score of the field of view is lower than the preset threshold, further analysis and processing of the field of view are cancelled, ensuring the accuracy of the statistical analysis process of inclusions and improving the inclusion recognition efficiency; when the method is implemented, the value range of the preset threshold is 60-100, and the total ideal score of each field of view is 100.

[0059] In the above step S108, according to the preset rules, the process of evaluating based on a number of identified deduction factors and calculating the score of any field of view is to perform deduction evaluations on each identified deduction factor in turn, and then calculate the score of the field of view, which is used to compare with the preset threshold; specifically, the calculation process is as follows:

[0060] Judge that the deduction factors existing in the field of view image include the aspect ratio of the second phase. It is specified that the aspect ratio of the second phase in a single field of view image shall not be higher than the first set value. Therefore, when the aspect ratio of the second phase is greater than the first set value, deductions are made according to the exceeding ratio of the aspect ratio, otherwise no deductions are made; among them, the value range of the first set value is 1-50, and the deduction range is 0-30; optionally, when the test sample has no rolling direction, the value range of the first set value is 1-2.

[0061] Judge that the deduction factors existing in the field of view image include the quantity of the second phase. It is specified that the quantity of the second phase in a single field of view image shall not be higher than the second set value. Therefore, when the quantity of the second phase is greater than the second set value, deductions are made according to the exceeding ratio of the quantity, otherwise no deductions are made; among them, the second set value is not less than 10, and the deduction range is 0-30.

[0062] Judge that the deduction factors existing in the field of view image include the direction of the second phase. It is specified that the deviation angle of the direction of the second phase in a single field of view image from the rolling direction shall not be higher than the third set value. Therefore, when the deviation angle of the direction of the second phase from the rolling direction is greater than the third set value, deductions are made according to the exceeding ratio of the deviation angle, otherwise no deductions are made; among them, the value range of the third set value is 10°-90°, and the deduction range is 0-50; optionally, the aspect ratio of the second phase used to judge the deviation angle is not less than 2, and when the test sample has no rolling direction, the third set value is set to 90°.

[0063] It is determined that the deduction factors existing in the field of view image include invalid detection regions. It is specified that the area of the second phase within a single field of view image and its proportion in the area of a single field of view shall not be higher than a fourth set value. Therefore, when the area of the second phase in the field of view and its proportion in the area of a single field of view are greater than the fourth set value, deductions are made according to the excess proportion of the said proportion; otherwise, no deductions are made. Among them, the value range of the fourth set value is 1% to 30%, and the deduction range is 0 to 50;

[0064] Calculate the difference between the total ideal score and the deduction items corresponding to each of the said deduction factors to obtain the score of the field of view. For example, Q = 100 - C - D - E - F, where Q is the total ideal score of a single field of view image, C is the deduction value after evaluating the morphology of the second phase, D is the deduction value after evaluating the quantity of the second phase, E is the deduction value after evaluating scratches, and F is the deduction value after evaluating the invalid detection region.

[0065] Based on the same inventive concept as the above method embodiment, there is also a metal material inclusion statistical analysis system in an embodiment of the present application. As Figure 7 shown is a framework schematic diagram of a metal material inclusion statistical analysis system. It can be seen from Figure 7 that the inclusion statistical analysis system includes: a specimen preparation module for preparing a test specimen containing the specimen to be tested and a reference material, and placing it into a test instrument pre - installed with an inclusion analysis system. Among them, the specimen to be tested is a polished metal block; a program setting module for setting an inclusion statistical analysis program according to the analysis requirements, including determining the rolling direction and photometric parameters of the specimen to be tested, the working parameters of the test instrument, and the area to be detected; a collection and recognition module for dividing the area to be detected into several fields of view, sequentially obtaining the field of view images of the specimen to be tested in each of the said fields of view according to the collection order, and identifying the deduction factors existing in each of the said field of view images. Among them, the deduction factors include the aspect ratio of the second phase, the quantity of the second phase, the direction of the second phase, and the invalid detection region; a calculation and judgment module for calculating and judging, according to a preset rule, the size relationship between the score of each of the said fields of view and a preset threshold, and determining that the field of view is valid when the score is not less than the preset threshold. Among them, the preset rule is a deduction rule formulated according to several deduction factors affecting the accurate statistics of inclusions in the field of view; an analysis and statistics module for performing energy spectrum analysis on the inclusions in the fields of view determined to be valid, and statistically analyzing the inclusions in several valid fields of view to complete the inclusion statistical analysis of the area to be detected.

[0066] This system is used to implement the steps of the metal material inclusion statistical analysis method disclosed in the above - mentioned embodiment, and those that have been described will not be elaborated here.

[0067] For example, the execution unit of the calculation and judgment module of the statistical analysis system for calculating the score of any one of the fields of view according to the preset rules includes: a first judgment unit, configured to judge that if the aspect ratio of the second phase is included in the deduction factors existing in the field of view image, then when the aspect ratio of the second phase is greater than the first set value, deductions are made according to the exceeding ratio of the aspect ratio, otherwise no deductions are made; wherein, the value range of the first set value is 1 to 50, and the deduction range is 0 to 30; a second judgment unit, configured to judge that if the number of the second phases is included in the deduction factors existing in the field of view image, then when the number of the second phases is greater than the second set value, deductions are made according to the exceeding ratio of the number, otherwise no deductions are made; wherein, the second set value is not less than 10, and the deduction range is 0 to 30; a third judgment unit, configured to judge that if the direction of the second phase is included in the deduction factors existing in the field of view image, then when the deviation angle between the direction of the second phase and the rolling direction is greater than the third set value, deductions are made according to the exceeding ratio of the deviation angle, otherwise no deductions are made; wherein, the value range of the third set value is 10° to 90°, and the deduction range is 0 to 50; a fourth judgment unit, configured to judge that if an invalid detection area is included in the deduction factors existing in the field of view image, then when the ratio of the area of the second phase in the field of view to the area of a single field of view is greater than the fourth set value, deductions are made according to the exceeding ratio of the ratio, otherwise no deductions are made; wherein, the value range of the fourth set value is 1% to 30%, and the deduction range is 0 to 50; a calculation unit, configured to calculate the difference between the total ideal score value and the deduction items corresponding to each of the deduction factors, and obtain the score of the field of view.

[0068] The following further specifically introduces the method for statistically analyzing inclusions in metal materials disclosed in the present invention in conjunction with specific embodiments.

[0069] Embodiment 1

[0070] (1) Preparation of the test sample

[0071] ① Select a X65MS pipeline steel plate, cut and make it into a block sample of 16mm * 10mm * 8mm, where the long side direction is the rolling direction, and 16mm * 10mm is the surface to be detected; perform grinding and polishing on the surface to be detected, and paste an aluminum tape at a corner of the surface to be detected as a reference material to obtain the test sample;

[0072] ② Put the test sample with the reference material pasted in ① into a scanning electron microscope;

[0073] (2) Setting of the inclusion statistics program

[0074] ① Respectively set the gray value A of the matrix material to 200 and the gray value B of the reference material to 60;

[0075] ②Set the acquisition area as the entire detection surface of the sample to be tested, that is, 16 mm * 10 mm, and detect inclusions with a minimum size ≥ 2 μm;

[0076] ③Adjust the brightness of the scanning electron microscope by 50.8% and the contrast by 36.7% according to the gray values of the matrix-reference in ①.

[0077] (3) Setting of rolling direction and scoring criteria

[0078] ①Mark the 16-mm direction as the rolling direction of the sample;

[0079] ②Set the preset threshold M = 75 for evaluating the validity of the field of view;

[0080] ③Set the first set value = 18, the second set value = 25, the third set value = 15°, and the fourth set value = 10% in the preset rules; among them, the original thickness of the X65MS pipeline steel plate is 22 mm, the thickness of the mother plate is 280 mm, and the compression ratio is 22 mm / 280 mm = 92.14%. After rolling, the aspect ratio of spherical inclusions is about 280 / 22 = 12.73. Considering the deformation allowance of non-spherical inclusions, the first set value is determined to be 18; refer to Method B in GB / T 10561-2023 "Steel - Determination of non-metallic inclusions - Micrographic method of standard rating diagrams" to grade the inclusions in the entire detection area of the sample. The rating of D-type inclusions with a minimum size ≥ 2 μm is 2.0. Considering that the electron microscope has higher resolution, the second set value is determined to be 25; in addition, the value of the second set value also needs to be set according to the minimum size of the inclusions. The smaller the detected inclusion size, the larger the corresponding second set value, and the larger the detected size, the smaller the corresponding second set value; secondly, the third set value is determined according to the situation of the field of view image of the sample placed in the scanning electron microscope. The third set value should be less than the deviation angle and is usually set as the median of the deviation angle; the fourth set value can be set according to experience. The area ratio of the second-phase region in the field of view should not be higher than a certain value. If it exceeds, it is considered that there is foreign object intrusion or it exceeds the effective recognition area, and the data in this area is not credible; in this experiment, it is set that when the area of the second-phase region in the field of view exceeds 10% of the field of view area, the data in this area is not credible and this field of view is excluded.

[0081] (4) Acquisition and validity evaluation of images of the area to be tested

[0082] ①Divide the area to be tested into 1000 fields of view, and the area of a single field of view is 0.16 mm 2 ;

[0083] ②Obtain the field of view images of each field of view in the area to be tested in the acquisition order respectively;

[0084] ③Identify the field of view images obtained in ②, extract and identify the deduction factors;

[0085] ④According to the preset rules, after scoring each deduction factor in ③ respectively, calculate the difference Q between the total ideal score and each deduction item, and obtain Q = 53;

[0086] ⑤Compare Q in ④ with the preset threshold M = 75. Since Q < M, it indicates that this field of view affects the statistical accuracy of inclusions and takes a long time. Therefore, this field of view is excluded and the identification of the next field of view is carried out;

[0087] ⑥Repeat ② - ⑤;

[0088] ⑦Judge the validity of all fields of view in the area to be measured.

[0089] (5) Inclusion statistics

[0090] Statistics show that 73 fields of view have scores lower than 75. After exclusion, 927 effective fields of view remain; perform energy spectrum analysis of inclusions on the determined effective fields of view, and a total of 4,142 inclusions are identified.

[0091] The method and system for statistical analysis of inclusions in metal materials disclosed by the present invention identify features in the images of each field of view. When there are many abnormal features in the detected field of view, such as non-sample areas, foreign objects, polishing materials, etc., skip the energy spectrum analysis of this field of view and perform the detection of the next field of view; compared with the prior art, when counting inclusions, a large amount of time is consumed in the fields of view with poor sample preparation effects, and additional non-inclusions are introduced, resulting in data distortion. The analysis efficiency and accuracy are significantly improved.

[0092] Although the present invention has been disclosed above with preferred embodiments, it is not intended to limit the present invention. Those with ordinary knowledge in the technical field to which the present invention belongs can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be subject to that defined by the claims.

Claims

1. A statistical analysis method for metal material inclusions, characterized in that: The steps include: A sample to be tested comprising a sample to be tested and a reference material is prepared and placed in a testing instrument, wherein the testing instrument is pre-installed with an inclusion analysis system; wherein the sample to be tested is a metal block that has been polished; According to the analysis requirements, set up the inclusion statistical analysis procedure, including determining the rolling direction and photometric parameters of the sample to be tested, the working parameters of the test instrument and the area to be tested; Divide the area to be tested into several fields of view, obtain the field of view images of the sample to be tested in each field of view in the acquisition order, and identify the deduction factors existing in each field of view image; wherein the deduction factors include the aspect ratio of the second phase, the number of the second phase, the direction of the second phase and the invalid detection area; According to a preset rule, the score of each field of view and the preset threshold are calculated and determined, and when the score is not less than the preset threshold, the field of view is determined to be valid; wherein the preset rule is a deduction rule formulated according to several deduction factors that affect the accurate statistics of inclusions in the field of view; The inclusion energy spectrum analysis is performed on the field of view determined to be valid, and the valid inclusions in the field of view are counted to complete the inclusion statistical analysis of the area to be detected.

2. The method for statistical analysis of metal material inclusions according to claim 1, characterized in that: According to the preset rules, the process of calculating the score of any of the fields of view is: It is determined that the deduction factors existing in the field of view image include the aspect ratio of the second phase, and when the aspect ratio of the second phase is greater than a first set value, deduction is performed according to the excess ratio of the aspect ratio, otherwise no deduction is performed; wherein the first set value is in the range of 1 to 50, and the deduction range is 0 to 30; Determining that the deduction factors existing in the field of view image include the number of the second phase, when the number of the second phase is greater than a second set value, deducting points according to the excess ratio of the number, otherwise no deduction; wherein the second set value is not less than 10, and the deduction range is 0 to 30; It is determined that the deduction factors existing in the field of view image include the direction of the second phase, and when the deviation angle between the direction of the second phase and the rolling direction is greater than a third set value, deduction is performed according to the excess ratio of the deviation angle, otherwise no deduction is performed; wherein the value range of the third set value is 10° to 90°, and the deduction range is 0 to 50; It is determined that the deduction factors existing in the field of view image include an invalid detection area, then when the area of ​​the second phase in the field of view and the proportion of the area of ​​a single field of view are greater than a fourth set value, deduction is performed according to the excess proportion of the proportion, otherwise no deduction is performed; wherein the value range of the fourth set value is 1% to 30%, and the deduction range is 0 to 50; The difference between the ideal score total and the deduction items corresponding to each of the deduction factors is calculated to obtain the score of the field of view.

3. The method for statistical analysis of metal material inclusions according to claim 2, characterized in that: When the sample to be tested does not have a rolling direction, the first set value ranges from 1 to 2.

4. The method for statistical analysis of metal material inclusions according to claim 2, characterized in that: The aspect ratio of the second phase used to determine the deviation angle is not less than 2.

5. The method for statistical analysis of metal material inclusions according to claim 4, characterized in that: When the sample to be tested does not have a rolling direction, the third set value is 90°.

6. The method for statistical analysis of metal material inclusions according to claim 1, characterized in that: The areas of the several viewing fields divided into the area to be detected are equal.

7. The method for statistical analysis of metal material inclusions according to claim 1, characterized in that: The preset threshold value ranges from 60 to 100.

8. The method for statistical analysis of metal material inclusions according to claim 1, characterized in that: The photometric parameters of the sample to be tested are determined by setting the grayscale value of the substrate to 170-220 and the grayscale value of the reference material to 30-70, and the working parameters of the test instrument are determined by setting the brightness and contrast of the test instrument according to the grayscale values ​​of the substrate and the reference material.

9. A statistical analysis system for metal material inclusions, characterized in that: include: The sample preparation module is used to prepare the sample to be tested including the sample to be tested and the reference material, and put it into the testing instrument, in which the inclusion analysis system is pre-installed; wherein the sample to be tested is a metal block that has been polished; The program setting module is used to set the inclusion statistical analysis program according to the analysis requirements, including determining the rolling direction and photometric parameters of the sample to be tested, the working parameters of the test instrument and the area to be tested; An acquisition and identification module is used to divide the area to be detected into several fields of view, obtain the field of view images of the sample to be tested in each field of view in the acquisition order, and identify the deduction factors existing in each field of view image; wherein the deduction factors include the aspect ratio of the second phase, the number of the second phase, the direction of the second phase and the invalid detection area; A calculation and judgment module, used to calculate and judge the size of the score of each field of view and a preset threshold according to a preset rule, and judge the field of view to be valid when the score is not less than the preset threshold; wherein the preset rule is a deduction rule formulated according to a number of deduction factors that affect the accurate statistics of inclusions in the field of view; The analysis and statistics module is used to perform inclusion spectrum analysis on the field of view determined to be valid, count valid inclusions in a number of the fields of view, and complete the inclusion statistics analysis of the area to be detected.

10. The metal material inclusion statistical analysis system according to claim 9, characterized in that: The calculation and judgment module calculates the score of any of the fields of view according to a preset rule, and the execution unit includes: A first judging unit is used to judge whether the deduction factor in the field of view image includes the aspect ratio of the second phase, and when the aspect ratio of the second phase is greater than a first set value, deduction is performed according to the excess ratio of the aspect ratio, otherwise no deduction is performed; wherein the first set value is in the range of 1 to 50, and the deduction range is 0 to 30; A second judgment unit is used to judge that the deduction factor existing in the field of view image includes the number of the second phase, and when the number of the second phase is greater than a second set value, deduction is performed according to the excess ratio of the number, otherwise no deduction is performed; wherein the second set value is not less than 10, and the deduction range is 0 to 30; A third judgment unit is used to judge that the deduction factors existing in the field of view image include the direction of the second phase. When the deviation angle between the direction of the second phase and the rolling direction is greater than a third set value, deduction is performed according to the excess ratio of the deviation angle, otherwise no deduction is performed; wherein the value range of the third set value is 10° to 90°, and the deduction range is 0 to 50; A fourth judgment unit is used to judge that the deduction factors existing in the field of view image include an invalid detection area. When the area of ​​the second phase in the field of view and the proportion of the area of ​​a single field of view are greater than a fourth set value, deduction is performed according to the excess proportion of the proportion, otherwise no deduction is performed; wherein the value range of the fourth set value is 1% to 30%, and the deduction range is 0 to 50; The calculation unit is used to calculate the difference between the ideal score total value and the deduction items corresponding to each of the deduction factors to obtain the score of the field of view.

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