Statistical analysis method for non-metallic inclusions in steel

Abstract

The present application relates to a kind of steel non-metallic inclusion statistical analysis method, the method includes the following steps: step 1: sample non-metallic inclusion statistics;Step 2: each sample non-metallic inclusion distribution rule analysis;Step 3: to be evaluated furnace steel liquid non-metallic inclusion distribution rule analysis;Step 4: to be evaluated furnace steel liquid overall non-metallic inclusion volume average value calculation;Step 5: to be evaluated furnace steel liquid overall non-metallic inclusion mass calculation;Step 6: to be evaluated furnace steel liquid overall non-metallic inclusion total volume calculation;Step 7: to be evaluated furnace steel liquid non-metallic inclusion total number calculation;Step 8: to be evaluated furnace steel liquid non-metallic inclusion total number calculation in any interval.The present application obtains the total number of non-metallic inclusions in the steel to be evaluated furnace and the total number of non-metallic inclusions in any interval based on the principle of statistical analysis by the diameter distribution and total oxygen content of steel sample non-metallic inclusions.

Description

Technical Field

[0001] This invention relates to an analytical method, specifically a statistical analysis method for non-metallic inclusions in steel, belonging to the field of steelmaking technology. Background Technology

[0002] The presence of non-metallic inclusions in steel disrupts the continuity of the steel matrix, easily leading to inhomogeneity in steel composition and microstructure, thus affecting its mechanical properties and adversely impacting its physicochemical properties. In particular, large-sized non-metallic inclusions have a significant impact on steel properties. Therefore, high-quality steel has extremely strict requirements regarding the size and quantity of non-metallic inclusions. However, the prerequisite for controlling the quantity and size of non-metallic inclusions is understanding their distribution in molten steel.

[0003] Non-metallic inclusions are randomly distributed in molten steel, and it is basically impossible to directly measure the quantity and size distribution of non-metallic inclusions in molten steel. At present, the main methods for analyzing the quantity and size of non-metallic inclusions in molten steel are: (1) taking steel samples and using metallographic microscopes to detect and statistically analyze the quantity and size distribution of non-metallic inclusions, and using the number and size distribution of non-metallic inclusions per unit detection area to characterize the level of non-metallic inclusions in the molten steel of the selected batch; (2) taking steel samples and using large-sample electrolysis to extract inclusions, and statistically analyzing the quality and composition of non-metallic inclusions, and using the weight of non-metallic inclusions per unit steel mass to characterize the level of non-metallic inclusions in molten steel; (3) taking steel samples and using relevant equipment to detect the total oxygen content of the samples, and using it to characterize the level of non-metallic inclusions.

[0004] The above method (1) has the following problems: the steel sample taken is usually tens of grams, while the weight of the molten steel in the ladle is mostly around 200t. In particular, the number of large-sized non-metallic inclusions is scarce. Large-sized non-metallic inclusions are often not detected in the steel sample taken. Then, in terms of the size of the hot-rolled slag inclusion defect, there are large-sized non-metallic inclusions in the steel. The above method (2) has the following problems: during the washing and separation process, small-sized non-metallic inclusions are screened out. It is not possible to obtain all sizes of non-metallic inclusions in the molten steel of the heat to be evaluated. The above method (3) can only know the mass fraction of non-metallic inclusions in the molten steel, and cannot obtain the specific quantity and size distribution of non-metallic inclusions. It can be seen that there is currently no analytical detection method that can truly reflect the quantity and size distribution of all non-metallic inclusions in the molten steel.

[0005] A search revealed that Chinese patent "CN 113418921 A" discloses a method for calculating the quantity of non-metallic inclusions in steel. This method uses a metallographic microscope to statistically analyze inclusion information in each field of view, and uses the statistical results to calculate the quantity of inclusions of various sizes to characterize the level of inclusions in the steel. However, this method cannot solve the problem of the difficulty in detecting large-sized inclusions. Chinese patent "CN112730491A" discloses a statistical analysis method for inclusions, which aims to solve the problem of the statistical quantity of inclusions in samples being too large in existing technologies, but does not consider the overall level of inclusions in the steel. Chinese patent "CN 111879784 A" discloses a new method for evaluating the cleanliness of steel. This method analyzes the largest-sized inclusions in different fields of view of small-sized components, and uses this to regress and give the size distribution law of non-metallic inclusions and the largest-sized inclusions in large-sized steel. However, this method does not provide the distribution law of inclusions of all sizes. Chinese patent "CN 111860176 A" discloses a method for quantitative statistical distribution characterization of non-metallic inclusions across the entire field of view. This method establishes a target detection model to identify and locate non-metallic inclusions in metallic materials across the entire field of view, aiming to improve identification accuracy and avoid errors caused by manual identification. Chinese patent "CN 110609042 A" discloses a method for predicting the largest inclusion size in steel. This method uses the largest inclusion size in all fields of view and establishes a prediction model for the largest inclusion size in steel using the maximum probability density function, but it cannot provide the number of the largest inclusion size. Chinese patent "CN 10983904 A" discloses a method for characterizing the distribution of non-metallic inclusions in large steel ingots using electrolysis. This method involves cutting multiple thin plate-shaped samples from the steel ingot to be surfaced, electrolyzing and collecting the number of non-metallic inclusions in different particle size ranges of each sample, and presenting the number density of non-metallic inclusions on the steel ingot surface in the form of a scatter plot or cloud map. Chinese patent CN105651217A discloses a statistical calculation method for the size of non-metallic inclusions in large-volume steel. This method uses metallographic testing to statistically analyze the size of inclusions in several metallographic samples, employs a Pareto distribution function to describe the size distribution of non-metallic inclusions, and obtains the size information of non-metallic inclusions in large-volume steel. However, this method cannot determine the number of the largest inclusions. Currently, no similar patents or documents have been found. Summary of the Invention

[0006] This invention addresses the problems existing in the prior art by providing a statistical analysis method for non-metallic inclusions in steel. This method employs metallographic analysis to statistically analyze the size distribution of non-metallic inclusions in the steel sample. Based on this, a log-normal distribution function is constructed. This log-normal distribution function is then used as the probability density distribution function for the diameter of non-metallic inclusions in the molten steel of the heat to be evaluated, thereby obtaining the diameter distribution pattern of non-metallic inclusions in that heat. Simultaneously, the average (expected) volume of non-metallic inclusions is calculated based on the probability density distribution of the non-metallic inclusion diameter. Combined with the total oxygen content of the steel sample, the total number of non-metallic inclusions in the molten steel is calculated using the density formula. The probability density distribution function of the non-metallic inclusion diameter and the total number of inclusions characterize the actual level of non-metallic inclusions in the molten steel of the heat to be evaluated, providing a theoretical basis for controlling the cleanliness of molten steel.

[0007] To achieve the above objectives, the technical solution of the present invention is as follows: a statistical analysis method for non-metallic inclusions in steel, the method comprising the following steps:

[0008] Step 1: Statistical analysis of non-metallic inclusions in the samples. Multiple steel samples are taken from the molten steel in the heat to be evaluated. The steel samples are then cut, processed, and polished. The number and diameter of non-metallic inclusions on the polished surface of each steel sample are automatically detected and counted using a metallographic microscope.

[0009] Step 2: Analysis of the distribution pattern of non-metallic inclusions in each sample. Information on non-metallic inclusions in each steel sample is summarized to obtain the quantity and diameter of each non-metallic inclusion in the samples taken from the furnace to be evaluated. Simultaneously, the diameters of the aforementioned non-metallic inclusions are grouped, and a frequency histogram of non-metallic inclusion diameters is obtained.

[0010] Step 3: Analysis of the distribution pattern of non-metallic inclusions in the molten steel of the heat to be evaluated. It is assumed that the diameter distribution pattern of non-metallic inclusions in the molten steel of the heat to be evaluated is the same as that of the non-metallic inclusions in the sample taken. Assuming that the diameter (x) distribution of non-metallic inclusions in the molten steel conforms to a log-normal distribution, its probability density function P(x) can be expressed as follows. Where μ and σ represent the expected value (mean) and standard deviation of the diameter of non-metallic inclusions in the molten steel, respectively, and are undetermined parameters of the probability density distribution function of the non-metallic inclusion diameter. Based on fitting the probability density distribution function of the diameter using the frequency histogram of the non-metallic inclusion diameter, the two parameters μ and σ are determined, thus obtaining the distribution pattern of non-metallic inclusions in the molten steel of the heat to be evaluated.

[0011]

[0012] Step 4: Average volumetric value of total non-metallic inclusions in the molten steel of the heat to be evaluated (V aveThe calculation is performed based on the probability density distribution function of the diameter of non-metallic inclusions. The average volume of the total non-metallic inclusions is derived using the formula below. The average volume of non-metallic inclusions in the undetermined furnace batch is then calculated using this formula.

[0013]

[0014] Step 5: Calculation of the total non-metallic inclusion mass in the molten steel of the heat to be evaluated. Based on the total oxygen content, free oxygen content, and types of non-metallic inclusions in the molten steel, the total mass of all non-metallic inclusions in the heat to be evaluated is calculated.

[0015] Step 6: Calculation of the total volume of non-metallic inclusions in the molten steel of the heat to be evaluated. Based on the density formula, the total volume of all non-metallic inclusions in the heat to be evaluated is calculated according to the density of the non-metallic inclusions.

[0016] Step 7: Calculate the total number of non-metallic inclusions in the molten steel of the heat to be evaluated. Based on the following formula relating the total volume of all non-metallic inclusions in the heat to be evaluated to its average volume, calculate the total number of non-metallic inclusions in the molten steel of the heat to be evaluated.

[0017]

[0018] Step 8: Calculate the total number of non-metallic inclusions in any interval of the molten steel in the heat to be evaluated. Using the probability density distribution function of the diameter of non-metallic inclusions in the molten steel of the heat to be evaluated and the total number of inclusions to characterize the true level of non-metallic inclusions in that heat, the number of non-metallic inclusions in any diameter interval [a, b] of the molten steel in the heat to be evaluated can be expressed as:

[0019]

[0020] Compared with the prior art, the present invention has the following advantages: the present invention obtains the diameter probability density distribution function and the total number of non-metallic inclusions in the molten steel based on the frequency histogram of the diameter of non-metallic inclusions in the steel sample taken from the furnace to be evaluated and the total oxygen content in the molten steel. That is, the present invention obtains the total number of non-metallic inclusions in the steel of the furnace to be evaluated and the total number of non-metallic inclusions in any interval based on the statistical analysis principle through the diameter distribution of non-metallic inclusions in the steel sample and the total oxygen content; (1) the present invention gives the probability density distribution function of the diameter of non-metallic inclusions in the molten steel of the furnace to be evaluated based on the statistical principle and the frequency histogram of the diameter of non-metallic inclusions in the sample of the furnace to be evaluated; (2) the present invention gives the calculation formula of the total number of non-metallic inclusions in the molten steel based on the statistical principle, and the total number of non-metallic inclusions in the furnace to be evaluated can be obtained by using this formula and the total oxygen content in the molten steel; (3) the probability density distribution function and the total number of non-metallic inclusions in the diameter obtained by the present invention can be used to obtain the number of non-metallic inclusions in any diameter range. (4) More importantly, the method of the present invention can be used to evaluate the quantity of large-size inclusions in the furnace to be evaluated. Attached Figure Description

[0021] Figure 1 Histogram of non-metallic inclusion diameters in samples taken from the first heat of ultra-low carbon steel in this invention;

[0022] Figure 2 In Example 1 of this invention, the density distribution function curve of the diameter histogram of non-metallic inclusions in ultra-low carbon steel samples was fitted.

[0023] Figure 3 Histogram of non-metallic inclusion diameters in samples taken from the second heat of ultra-low carbon steel in this invention;

[0024] Figure 4 In Example 2 of this invention, the density distribution function curve of the diameter histogram of non-metallic inclusions in ultra-low carbon steel samples was fitted. Detailed Implementation

[0025] To enhance understanding of the present invention, the embodiments will be described in detail below with reference to the accompanying drawings.

[0026] This invention selects a specific batch of aluminum-killed ultra-low carbon steel as the research object, and applies the method of this invention to obtain the level of non-metallic inclusions in the molten steel of that batch. Specific embodiments are as follows:

[0027] Example 1: See Figures 1-2 A statistical analysis method for non-metallic inclusions in steel, the method comprising the following steps:

[0028] Step 1: Take four bucket samples of the ultra-low carbon steel from this batch. Then cut, process and polish the steel samples. Use a metallographic microscope to automatically detect and count the number of non-metallic inclusions on the polished surface of the four ultra-low carbon steel samples and the diameter of each non-metallic inclusion.

[0029] Step 2: Information on non-metallic inclusions from the four ultra-low carbon steel samples was compiled to obtain the size information of the non-metallic inclusions. The minimum diameter of the non-metallic inclusions was 1.22 μm, the maximum diameter was 32.71 μm, and the total number was 7111. Simultaneously, the non-metallic inclusion diameters were grouped into groups of 2 μm, and frequency histograms of the non-metallic inclusion diameters in each group were obtained, as shown below. Figure 1 As shown.

[0030] Step 3: Based on Figure 1 The frequency histogram of the diameter of non-metallic inclusions was fitted with a log-normal distribution function, and the values ​​of the two parameters μ and σ were obtained as 0.62 and 0.59, respectively. Substituting these parameters into the above log-normal distribution function expression, the probability density distribution function of the diameter of non-metallic inclusions in this batch of ultra-low carbon steel was obtained.

[0031]

[0032] Step 4: Substitute the above two parameters into the calculation formula for the expected volume of non-metallic inclusions derived in this invention to obtain the average volume of non-metallic inclusions in this batch of ultra-low carbon steel as 16.11 μm. 3 .

[0033] Step 5: The total oxygen content of the ultra-low carbon steel in this batch is 21×10⁻⁶. -4 % (mass fraction), free oxygen content 3×10 -4 The non-metallic inclusions in aluminum-killed ultra-low carbon steel are Al2O3. The total weight of the molten steel in this furnace is 250t, so the total mass of the non-metallic inclusions Al2O3 is 9.56kg.

[0034] Step 6: Based on the density formula and the density of Al2O3 inclusions being 3990 kg / m³ 3 The total volume of all non-metallic inclusions in the undetermined furnace batch was calculated to be 2.40 × 10⁻⁶. 15 μm 3 .

[0035] Step 7: Based on the relationship between the total volume of all non-metallic inclusions in the undetermined heat and the expected volume value, calculate the total number of non-metallic inclusions in the molten steel of the undetermined heat: 1.49 × 10⁻⁶. 14 indivual.

[0036] Step 8: The total amount of non-metallic inclusions in this batch of ultra-low carbon steel is 1.49 × 10⁻⁶. 14If the diameter of the non-metallic inclusions follows a log-normal distribution with μ = 0.62 and σ = 0.59, then the number of non-metallic inclusions in any diameter interval [a, b] of the ultra-low carbon steel in a batch is:

[0037]

[0038] Example 2: See Figures 3-4 A statistical analysis method for non-metallic inclusions in steel, the method comprising the following steps:

[0039] Step 1: Take 5 bucket samples of the ultra-low carbon steel from this batch, then cut, process and polish the steel samples. Use a metallographic microscope to automatically detect and count the number of non-metallic inclusions on the polished surface of the 5 ultra-low carbon steel samples and the diameter of each non-metallic inclusion.

[0040] Step 2: Information on non-metallic inclusions from the five ultra-low carbon steel samples was compiled to obtain the size information of the non-metallic inclusions. The minimum diameter of the non-metallic inclusions was 1.13 μm, the maximum diameter was 37.95 μm, and the total number was 8145. Simultaneously, the non-metallic inclusion diameters were grouped into groups of 2 μm, and frequency histograms of the non-metallic inclusion diameters in each group were obtained, as shown below. Figure 3 As shown,

[0041] Step 3: Based on Figure 3 The frequency histogram of the diameter of non-metallic inclusions was fitted with a log-normal distribution function, yielding values ​​of μ and σ of 0.55 and 0.45, respectively. Substituting these parameters into the aforementioned log-normal distribution function expression, the probability density distribution function of the diameter of non-metallic inclusions in this batch of ultra-low carbon steel was obtained.

[0042]

[0043] Step 4: Substitute the above two parameters into the calculation formula for the expected volume of non-metallic inclusions derived in this invention to obtain the average volume of non-metallic inclusions in this batch of ultra-low carbon steel as 6.78 μm. 3 .

[0044] Step 5: The total oxygen content of the ultra-low carbon steel in this batch is 16×10⁻⁶. -4 % (mass fraction), free oxygen content 3×10 -4 The non-metallic inclusions in aluminum-killed ultra-low carbon steel are Al2O3. The total weight of the molten steel in this furnace is 250t, so the total mass of the non-metallic inclusions Al2O3 is 6.91kg.

[0045] Step 6: Based on the density formula and the density of Al2O3 inclusions being 3990 kg / m³ 3 The total volume of all non-metallic inclusions in the undetermined furnace batch was calculated to be 1.73 × 10⁻⁶. 15 μm3 .

[0046] Step 7: Based on the relationship between the total volume of all non-metallic inclusions in the undetermined heat and the expected volume value, calculate the total number of non-metallic inclusions in the molten steel of the undetermined heat: 2.55 × 10⁻⁶. 14 indivual.

[0047] Step 8: The total amount of non-metallic inclusions in this batch of ultra-low carbon steel is 2.55 × 10⁻⁶. 14 If the diameter of the non-metallic inclusions follows a log-normal distribution with μ = 0.55 and σ = 0.45, then the number of non-metallic inclusions in any diameter interval [a, b] of the ultra-low carbon steel in a batch is:

[0048]

[0049] It should be noted that the above embodiments are not intended to limit the scope of protection of the present invention. Equivalent transformations or substitutions made based on the above technical solutions all fall within the scope of protection of the claims of the present invention.

Claims

1. A statistical analysis method for non-metallic inclusions in steel, characterized in that, The method includes the following steps: Step 1: Non-metallic inclusion count of samples; Multiple steel samples are taken from the molten steel of the furnace to be evaluated. The steel samples are then cut, processed, and polished. A metallographic microscope is used to automatically detect and count the number and diameter of non-metallic inclusions on the polished surface of each steel sample. Step 2: Analysis of the distribution pattern of non-metallic inclusions in each sample; The information on non-metallic inclusions in each steel sample is summarized to obtain the quantity and diameter of non-metallic inclusions in the samples taken from the furnace to be evaluated. Simultaneously, the diameters of the non-metallic inclusions are grouped, and a frequency histogram of non-metallic inclusion diameters is obtained. Step 3: Analysis of the distribution pattern of non-metallic inclusions in the molten steel of the heat to be evaluated; assuming that the diameter distribution pattern of non-metallic inclusions in the molten steel of the heat to be evaluated is the same as that of the non-metallic inclusions in the sample taken, and assuming that the diameter x of the non-metallic inclusions in the molten steel follows a log-normal distribution, its probability density function P(x) can be expressed as follows, where μ and σ represent the mean and standard deviation of the diameter of the non-metallic inclusions in the molten steel, respectively, and are the undetermined parameters of the probability density distribution function of the non-metallic inclusion diameter. Based on fitting the probability density distribution function of the diameter using the frequency histogram of the non-metallic inclusion diameter, the two parameters μ and σ are determined, thus obtaining the distribution pattern of non-metallic inclusions in the molten steel of the heat to be evaluated. ； Step 4: Average volumetric value V of total non-metallic inclusions in the molten steel of the heat to be evaluated. ave Calculate the probability density distribution function P(x) based on the diameter of the non-metallic inclusion, and then calculate the expected value E(x) of the cube of the diameter of the non-metallic inclusion. 3 ), calculate the average diameter of the non-metallic inclusions. This allows us to derive the average volume of the total non-metallic inclusions. The specific calculation formula is as follows: [Formula omitted for brevity]. Based on this formula, we can calculate the average volume of non-metallic inclusions for the undetermined furnace batch. ； Step 5: Calculate the total mass of non-metallic inclusions in the molten steel of the heat to be evaluated. Based on the total oxygen content, free oxygen content and types of non-metallic inclusions in the molten steel, calculate the total mass of all non-metallic inclusions in the heat to be evaluated. Step 6: Calculate the total volume of non-metallic inclusions in the molten steel of the heat to be evaluated. Based on the density formula, calculate the total volume V of all non-metallic inclusions in the heat to be evaluated according to the density of the non-metallic inclusions. T ; Step 7: Calculate the total number of non-metallic inclusions in the molten steel of the heat to be evaluated. Based on the following formula relating the total volume of all non-metallic inclusions in the heat to be evaluated to the average volume, calculate the total number N of non-metallic inclusions in the molten steel of the heat to be evaluated. T , ； Step 8: Calculate the total number of non-metallic inclusions in any interval of the molten steel in the heat to be evaluated. The probability density distribution function of the diameter of the non-metallic inclusions in the molten steel of the heat to be evaluated and the total number of inclusions characterize the true level of non-metallic inclusions in that heat. Therefore, the number of non-metallic inclusions in any diameter interval [a, b] of the molten steel in the heat to be evaluated is expressed as: 。

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