A method for detecting the single-particle breakage characteristics of steel slag

Abstract

The application discloses a method for detecting single-particle crushing characteristics of steel slag, and relates to the technical field of solid waste material particle detection, and is based on the influence of morphological effect on the single-particle crushing strength of steel slag. The single-particle crushing detection of steel slag is carried out under different loading rates and set quantitative morphological conditions, the single-particle crushing mode and crushing energy are obtained, the crushing strength of the particle is analyzed by using the Weibull distribution, and the influence of the morphological effect and the external loading rate on the single-particle crushing of steel slag is analyzed by using fitting discreteness. The method for detecting single-particle crushing characteristics of steel slag provides theoretical guidance and technical support for whether the single-particle of steel slag can be diversifiedly utilized as a new solid waste resource by the influence mechanism of particle morphological effect and loading speed on the crushing strength, crushing mode and energy dissipation law.

Description

Technical Field

[0001] The present invention relates to the technical field of solid waste material particle detection, and in particular to a method for detecting the crushing characteristics of single steel slag particles. Background Art

[0002] Steel slag is a typical byproduct of the smelting process. Its production is enormous, yet its utilization rate is low. Unused slag is often stockpiled or landfilled, which not only consumes significant land resources but also poses a potential threat to the environment. However, due to its inherent strength, wear resistance, skid resistance, high alkalinity, and low cost, it can be used as a high-quality building material, roadbed material, and other materials after proper processing, achieving green resource utilization.

[0003] The single-particle compression indoor test aims to study the failure mode and compression failure mechanism of brittle materials under impact load, including many influencing factors such as shape and particle size. Domestic and foreign scholars mostly use the Weibull function to study the randomness of particle crushing strength, providing basic parameters for exploring the characteristics of factors affecting particles and establishing the constitutive relationship of granular materials.

[0004] Currently, research on single-particle crushing has largely focused on the influence of single factors, such as morphology and size effects, on the crushing characteristics of single particles, and most of this research has been based on calcareous soil and sand particles. However, single steel slag particles inherently possess highly irregular particle morphology and sufficiently excellent mechanical properties, making it difficult to obtain effective results by studying the influence of a single factor on the crushing strength of steel slag particles. Therefore, it is urgent to develop a systematic method for determining the crushing characteristics of single steel slag particles that comprehensively considers the effects of particle morphology and external loading rate. This method, combining experimental research with numerical simulation, can provide theoretical and experimental evidence for the feasibility of steel slag particles as a new type of road or railway ballast material. Summary of the Invention

[0005] In response to the above-mentioned technical problems to be solved, the present invention provides a method for detecting the crushing characteristics of single steel slag particles. Through the influence mechanism of particle morphology effect and loading speed on crushing strength, crushing mode and energy dissipation law, theoretical guidance and technical support are provided for whether single steel slag particles can be used in a diversified manner as a new type of solid waste resource.

[0006] In order to solve the above technical problems, the technical solution proposed by the present invention is:

[0007] A method for detecting single particle crushing characteristics of steel slag comprises the following steps:

[0008] Step S1, screening the steel slag particles to select at least four groups of single steel slag particles according to different particle sizes;

[0009] Step S2, each group of steel slag single particles of different particle sizes screened in step S1 is further grouped according to different morphologies;

[0010] Step S3, further refining the steel slag single particles grouped for the second time in step S2, and setting different external loading rates for each group of steel slag single particles after grouping;

[0011] Step S4: morphologically quantify the slag single particles of each group with different morphologies selected in step S2, selecting three main dimension parameters: the major axis L, the minor axis S, and the intermediate long axis I to determine the relationship between shape, strength, and crushing mode; obtain the external surface shape feature information to obtain a three-dimensional numerical image of each group of particles;

[0012] Step S5, performing single-particle crushing on each group of steel slag single particles with different shapes and to be subjected to different external loading rates in step S3, and obtaining relevant crushing strength data of the steel slag single particles;

[0013] Step S6, classifying the crushing modes of the single slag particles crushed in step S5, and analyzing different curve types caused by different morphologies and loading rates;

[0014] Step S7, deriving the crushing energy of each group of steel slag single particles based on the crushing strength data obtained after the single particle crushing in step S5, where the single particle crushing energy is defined according to the load-displacement curve relationship;

[0015] Step S8, based on the crushing strength data obtained from the single particle crushing test in step S5, using Weibull distribution statistics, calculate the relationship between the survival probability and characteristic stress of a single slag particle under different shapes and different external loading rates;

[0016] Step S9: Based on the relationship between the survival probability and the characteristic stress in step S8, further describe the Weibull distribution function of the single particle crushing strength distribution, use its distribution curve to judge the discreteness of the single particle crushing strength, and obtain m and R by fitting. 2 value, m is the Weibull modulus, R 2 is the curve fitting degree.

[0017] As a further improvement of the above technical solution:

[0018] Preferably, in step S2, the different forms include at least irregular spherical particles, strip-shaped particles, and flake-shaped particles.

[0019] Preferably, in step S4, the morphology quantification is to calculate the value range of the shape parameters of single slag particles of different morphologies through flatness and elongation, and determine the relationship between shape-strength-crushing mode.

[0020] Preferably, the step S8 specifically includes the following steps:

[0021] S8-1, Weibull standard expression function is:

[0022] ;

[0023] Where, is the crushing strength of single particle of steel slag, is the shape parameter, is the scale parameter;

[0024] S8-2, Calculate the particle crushing characteristic stress based on the assumption of Weibull statistics The cumulative probability of survival under , that is, the survival probability, is expressed as:

[0025] ;

[0026] Where, is the survival probability of the particle, ,in It represents the probability of particle survival, that is, the ratio of the number of unbroken particles to the total number of particles. Indicates the number of unbroken particles, It represents the ratio of the total number of particles; The particle crushing characteristic stress corresponding to the test load is the actual stress value that causes the particle crushing. and the particle size d, where The maximum peak of the load-displacement curve is taken as the particle breakage point, and the corresponding load is the maximum load. The particle size d can be calculated by its long axis (L), medium-long axis (I) and short axis (S). to determine; is the characteristic destructive strength; m represents the Weibull modulus, which characterizes the discreteness of particle strength and is used to measure the dispersion of crushing strength. The larger the m value, the smaller the discreteness of particle strength.

[0027] S8-3, based on S8-1 and S8-2, the survival probability of a single slag particle under different crushing conditions and the particle crushing characteristic stress can be calculated. relationship.

[0028] Preferably, in step S9, the Weibull distribution function of the single particle crushing strength distribution is described as follows:

[0029] The equation for the Weibull modulus m value is obtained by taking the logarithm twice on both sides of the equation for the probability of survival in step S8. The discreteness of the single particle crushing strength is judged by using its distribution curve. Linear regression equation, Represents the particle characteristic stress The modulus m reflects the concentration of the material's probability distribution of breakage. The larger the modulus, the more concentrated the probability distribution of breakage.

[0030] The method for detecting the crushing characteristics of single steel slag particles provided by the present invention has the following advantages over the prior art:

[0031] The present invention's method for detecting the crushing characteristics of single steel slag particles is based on the influence of morphological effects on the crushing strength of single steel slag particles. By testing single steel slag particle crushing at different loading rates and under pre-defined quantitative morphological conditions, the method obtains the single-particle crushing pattern and crushing energy. The method also uses a Weibull distribution to analyze the crushing strength of particles and its fitted discreteness to analyze the influence of morphological effects and external loading rates on the crushing of single steel slag particles. The present invention has a simple calculation principle and concise and clear calculation content, effectively reflecting the actual particle crushing characteristics. This method provides an effective technical means for further understanding the mechanical behavior of brittle granular materials and provides theoretical and experimental evidence for the feasibility of steel slag particles as a new type of highway or railway ballast material. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is the three-dimensional scanning imaging of a single steel slag particle described in the present invention.

[0033] Figure 2 This is the load-displacement curve of a single spherical steel slag particle under different external loading rates described in the present invention.

[0034] Figure 3 The load-displacement curves of a single steel slag particle with v = 1 mm / s under different shapes described in the present invention.

[0035] Figure 4 Schematic diagram of the calculation of the crushing energy of a single steel slag particle according to the present invention.

[0036] Figure 5 The graph shows the residual probability and characteristic stress distribution curve of a single steel slag particle in different forms according to the present invention.

[0037] Figure 6 The graph shows the survival probability and characteristic stress distribution curve of a single steel slag particle at different loading rates.

[0038] Figure 7 It is the Weibull distribution fitting curve of the steel slag single particle strength described in the present invention. DETAILED DESCRIPTION

[0039] The following is a detailed description of the specific embodiments of the present invention. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present invention and are not intended to limit the present invention.

[0040] The method for detecting the crushing characteristics of single steel slag particles of the present invention is based on the influence of morphological effects on the crushing strength of single steel slag particles. Single particle crushing tests are carried out under different loading rates and set quantitative morphological conditions. The single particle crushing mode and crushing energy are studied based on the displacement-load data obtained from the tests. The crushing strength of the particles is analyzed based on the Weibull distribution, and the influence of morphological effects and external acceleration rate on the crushing of single particles is analyzed based on its discreteness.

[0041] The specific steps include:

[0042] Step S1: manually screening the steel slag particles to screen out multiple groups of single steel slag particles in different particle size ranges.

[0043] In this embodiment, the slag particles are screened to obtain four particle size groups: Z1 [2.36-4.75], Z2 [4.75-9.5], Z3 [9.5-16], and Z4 [16-19]. The number of particles in each particle size range is required to be no less than 50.

[0044] Step S2: selecting and grouping the single slag particles in each group after screening according to different forms for a second time.

[0045] In this embodiment, particles of the Z3 [9.5-16] particle size group are selected, and three groups of steel slag single particles with different shapes are selected: irregular spherical particles, strip-shaped particles, and flake-shaped particles.

[0046] Step S3: refining and grouping each group of selected steel slag single particles.

[0047] After the morphological grouping according to step S2, each group of slag single particles is further divided into three groups of "low, medium and high" in this embodiment, which are divided into three groups of low speed loading 0.1 mm / s, medium speed loading 1 mm / s and high speed loading 5 mm / s.

[0048] Each group of steel slag single particles after refinement is set to a different external loading rate, named 1-1, 1-2, ..., Nn, where N is the number of groups of steel slag single particles with different morphologies after refinement, and n is the number of steel slag single particles to be tested in each group, and n=n1+n2+...n a , n1=n2=…=n a , a is the number of different external loading rate groups, and n1, n2, etc. are the number of single particles measured at each external loading rate, covering quasi-static to dynamic loading scenarios. In a static scenario, the loading plate on the instrument remains stationary at a loading rate of 0 mm / s. In a dynamic scenario, the loading plate moves downward at the set rate until it contacts the sample particle. The plate continues to press downward at the set rate, generating load-displacement data, until the particle breaks, at which point the test is terminated.

[0049] Step S4, quantify the morphology of each group of steel slag single particles of different shapes selected in step S2, first use a vernier caliper to manually measure the three main dimensional parameters of each group of particles, the long axis L, the short axis S, and the medium-long axis I, and select the flatness f = I / S (aspect ratio, that is, the ratio of the longest axis of the particle to the thickness of the particle) for irregular spherical, strip-shaped and flaky steel slag single particles to reflect the flatness of the particles; take the elongation e = L / I (length-to-width ratio, that is, the ratio of the longest axis of the particle to the medium-long axis of the particle) to reflect the slenderness of the particles. The value range of the shape parameters is calculated by the two commonly used shape characterization quantities of flatness and elongation to reveal the deep correlation between shape-strength-crushing mode. The different value ranges of the shape parameters represent three groups of different shapes. Based on three-dimensional scanning image acquisition technology, the Reality Composer scanner is used to obtain the external surface shape feature information to obtain a three-dimensional numerical image of each group of particles, such as Figure 1 As shown, Figure 1 (a) is an irregular spherical particle, (b) is a strip-shaped particle, and (c) is a flake-shaped particle, all stored in .stl file format.

[0050] Step S5, performing an indoor single particle crushing test on each group of steel slag single particles with different shapes and to be subjected to different external loading rates in step S3.

[0051] The crushing experiment includes the following:

[0052] (1) Before the test, the particles were set with their major axis L as the axial direction.

[0053] (2) Place it in the center of the lower base to keep it stable, and use the displacement control mode to adjust the speed of the upper pressure plate so that it first drops quickly and is adjusted to a position close to the particle surface. Then continue to slowly load and lower the lower pressure plate at a low displacement rate so that it is just in contact with the particle surface. At this time, the force value and displacement recorded by the computer data acquisition system are adjusted to "0.00".

[0054] (3) During the test, in order to analyze the effect of loading rate on the particle crushing characteristics, a rate-controlled loading method was adopted. Each group of particles was loaded with a single particle at a rate of 0.1 mm / min, 1 mm / min, and 5 mm / min. When the lower pressure plate descended to a certain stage at different rates, the single particle load-displacement curve showed a sudden drop in load, and the particles showed obvious splitting or crushing patterns. The test was immediately suspended, and the force-displacement curve of the single particle crushing process was obtained.

[0055] (4) After the test, the real-time force and displacement data collected by the computer (the force value at the moment of crushing is the crushing strength of the particle) are exported and the particle morphology and fragment distribution after crushing are recorded. Then, the next particle test is carried out. Each set of variables is repeated 10 times to ensure data reliability. A total of 90 sets of test results are obtained to obtain the relevant crushing strength data of single steel slag particles.

[0056] Step S6, classify the crushing modes of the single slag particles after the test in step S5, and analyze the different curve types that may be caused by different morphologies and external loading rates, such as Figure 2 、 Figure 3 The single and interactive comparison of the single slag particle crushing patterns and their load-displacement curves obtained with different morphologies and rates is used to determine whether the two have an impact on the internal stress distribution of the material.

[0057] Figure 2 is the load-displacement curve of a single spherical steel slag particle under different external loading rates, Figure 2 (a) is the load-displacement curve of a single spherical particle at an external loading rate of V=0.1mm / s, (b) is the load-displacement curve of a single spherical particle at an external loading rate of V=1mm / s, and (c) is the load-displacement curve of a single spherical particle at an external loading rate of V=0.1mm / s. This shows that steel slag has high compressive strength, and its high loading rate may lead to more sudden breakage. The curve has a high peak, is dominated by brittle fracture, and has a strong load-bearing capacity; while the low loading rate curve is flat, and has a stronger load-bearing capacity. Figure 3 Figure 3 is the load-displacement curve of a single steel slag particle under different shapes at v=1mm / s. The curve shows that irregular spherical particles have more uniform stress distribution and can withstand greater loads. Compared with spherical particles, strip-shaped particles have higher peak loads under the same displacement, more concentrated stress, and are prone to brittle fracture. This shows that the shape parameters of flatness f = I / S (aspect ratio) and elongation e = L / I (length-to-width ratio) also have a significant impact on the single particle crushing mode.

[0058] Step S7, deriving the crushing strength data of the single particle crushing test in step S5, and using the displacement integral function to derive the crushing energy of each group of steel slag single particles The single particle crushing energy is defined according to the load-displacement curve relationship, where Indicates the crushing force, which is the load borne by a single particle crushing. Represents displacement. The schematic diagram of the single particle crushing energy distribution is shown in Figure 4 As shown, the shaded area represents the crushing energy of a single slag particle. Figure 4 This is a schematic diagram of the calculation of the crushing energy of a single steel slag particle. Figure 4(a) is the crushing energy distribution of irregular spherical particles at different external loading rates, and (b) is the crushing energy distribution of particles of different shapes when V=1mm / s. The smaller the area of ​​the shaded part of the curve, the smaller the single particle crushing energy, the more energy dissipation, and the stronger the load capacity.

[0059] In step S8, based on the crushing strength data obtained from the single particle crushing test in step S5, the relationship between the survival probability and characteristic stress of a single slag particle under different shapes and different external loading rates is calculated using Weibull distribution statistics. The derivation process is as follows:

[0060] S8-1, Weibull standard expression function is:

[0061] ;

[0062] Where, is the crushing strength of single particle of steel slag, is the shape parameter, is the scale parameter.

[0063] S8-2, based on the assumption of Weibull statistics, the cumulative distribution function (CDF) of the probability that the random variable is equal to or less than a certain value can be converted to obtain the characteristic stress of the slag particles in the particle crushing state. The cumulative probability of survival under , that is, the survival probability, is expressed as:

[0064] ;

[0065] Where, is the survival probability of the particle, ,in It represents the probability of particle survival, that is, the ratio of the number of unbroken particles to the total number of particles. Indicates the number of unbroken particles, It represents the ratio of the total number of particles; is the particle crushing characteristic stress corresponding to the test load, which is the actual stress value that causes the particle crushing and can be obtained by Calculated, where The maximum peak value of the load-displacement curve is taken as the particle breakage point, and the corresponding load is the maximum load. The particle size d passes through the long axis (L), the middle long axis (I) and the short axis (S). to determine; is the characteristic failure strength, and the characteristic stress level corresponding to the residual probability of the granular material is 37% (when the particle characteristic stress Equal to the characteristic destructive strength When ); m represents the Weibull modulus, which characterizes the discreteness of particle strength and is used to measure the dispersion of crushing strength. The larger the m value, the smaller the discreteness of particle strength.

[0066] S8-3, based on S8-1 and S8-2, the survival probability of a single slag particle under different crushing conditions and the particle crushing characteristic stress can be calculated. relationship, such as Figure 5 and Figure 6 As shown. The dotted line represents the survival probability of a single slag particle under characteristic stress. =37%, and the value corresponding to the intersection of its point with the peak crushing stress of each particle size is the characteristic stress of the particle of that particle size. It can be more clearly seen that under the same survival probability, the influence of morphology and external loading rate on the crushing stress intensity of a single particle is the same. Figure 5 The survival probability and characteristic stress distribution curves of single slag particles in different shapes are shown in the figure. It can be seen from the figure that under the same survival probability, the strength of irregular spherical particles is significantly higher than that of strip and flaky particles, and their internal stress distribution is more uniform. With the increase of flatness f and elongation e, the characteristic stress of flaky and strip particles gradually decreases, indicating that the particle shape significantly affects the characteristic stress. The crushing strength of single slag particles with different shapes is different. Irregular spherical particles (i.e., the flatness f is approximately equal to the range of elongation e) require the most energy and can withstand higher loads. Their characteristic stress is the largest, making them suitable for use in high-stress environments. Figure 6 The curves are the survival probability and characteristic stress distribution curves of single slag particles at different loading rates. The curves show that the overall trends of the curves at different speeds are similar, and there are slight differences in the specific values. However, as the loading rate of the single particle increases, its characteristic stress will not change significantly, and its discreteness needs to be further analyzed.

[0067] Step S9: Based on the relationship between the survival probability and the characteristic stress in step S8, further describe the Weibull distribution function of the single particle crushing strength distribution, use the steel slag single particle strength Weibull distribution curve to judge the discreteness of the single particle crushing strength, and fit to obtain the Weibull modulus m and the curve fitting degree R 2 value.

[0068] To further describe the Weibull distribution function of the single particle crushing strength distribution, the equation for the Weibull modulus m value can be obtained by taking the logarithm twice on both sides of the equation of the residual probability in step S8. It is convenient to use its distribution curve to judge the discreteness of the single particle crushing strength, and the equation for the Weibull modulus m value can be obtained. Linear regression equation, draw the single particle of steel slag Linear regression curve, such as Figure 7 As shown, Represents the particle characteristic stress . Figure 7 is the Weibull distribution fitting curve of steel slag single particle strength, Figure 7 (a) is the strength fitting of steel slag particles under different shapes, and (b) is the strength fitting of steel slag particles under different loading rates. The slope of the curve is the Weibull modulus m. The Weibull modulus m reflects the degree of concentration of the material's probability distribution of breakage. The larger the modulus, the more concentrated the probability distribution of breakage, indicating that the material is more uniform and more brittle. On the contrary, the smaller the modulus, the more dispersed the breakage distribution, the material is uneven and has high ductility. According to the curve fitting degree R 2 It can be proved that this method is feasible to study the crushing characteristics of single steel slag particles.

[0069] This demonstrates that the method presented here accurately infers that particle morphology significantly influences characteristic stress. Irregular spherical particles (i.e., those with a flattening factor f approximately equal to the elongation e) exhibit high crushing strength and are therefore suitable for use in high-stress environments. Furthermore, the loading rate modulates the energy release pattern, with the highest fit observed at high loading rates. Therefore, it is concluded that steel slag is feasible as a new type of road or railway ballast material.

[0070] Experimental verification

[0071] In this example, 90 single converter slag particles from the Z3 [9.5-16] particle size group were selected through screening tests. Three principal dimensions (L, S, and I) were manually measured for each particle using a vernier caliper. For irregular spherical, strip-shaped, and flake-shaped particles, the flattening ratio (f = I / S, i.e., the ratio of the particle's major axis to its minor axis) and the elongation (e = L / I, i.e., the ratio of the particle's longest axis to its major axis) were used to characterize the particle's slenderness. The ranges of these shape parameters were calculated, as shown in Table 1, to reveal the underlying relationship between shape, strength, and crushing mode. External surface shape features were acquired through scanning with Reality Composer, resulting in a three-dimensional numerical image of the particles, which was then stored in the .stl file format.

[0072] Table 1 Characterization quantities of single slag particle shape and classification of values

[0073]

[0074] Single-particle crushing tests were conducted on three different groups of steel slag particles: irregular spheres, strips, and flakes. Before the test, the particle was oriented with its major axis L at the center of the lower base to maintain stability. Using displacement control, the upper platen's velocity was adjusted, initially rapidly descending until it approached the particle surface. The lower platen was then slowly lowered at a low displacement rate until it contacted the particle surface. The force and displacement values ​​recorded by the computer data acquisition system at this point were set to "0.00."

[0075] To analyze the impact of loading rate on particle breakage characteristics, a rate-controlled loading method was used. Each group of particles was subjected to compression loading at three different speeds: low (0.1 mm / s), medium (1 mm / s), and high (5 mm / s). These loading scenarios ranged from quasi-static to dynamic. The specific test protocols are grouped as shown in Table 2 below. The test was paused when the lower platen descended at different rates to a certain point, indicating a sudden drop in the load-displacement curve for a single particle and a clear splitting or fragmentation pattern. This provided a force-displacement curve for the individual particle breakage process. After the test, the real-time force and displacement data collected by the computer (the force at the moment of breakage represents the particle's breakage strength) were exported and the particle morphology and fragment distribution after crushing were recorded. The next particle was then tested. Each variable was repeated 10 times to ensure data reliability, resulting in a total of 90 test results.

[0076] Table 2 External loading rate and shape comprehensive grouping of single slag particles

[0077]

[0078] After obtaining the relevant crushing strength data of single slag particles, the different curve types that may be caused by different morphologies and loading rates are analyzed. By comparing the single slag particle crushing patterns and their load-displacement curves obtained with different morphologies and different rates, it is determined that different particle morphologies have an impact on the internal stress distribution of the material, as shown in Table 3.

[0079] Table 3 Different curve types caused by different morphologies and loading rates of single slag particles

[0080]

[0081] Using the Weibull distribution to further transform and analyze the displacement-load curve data of single slag particles, we found that loading rate regulates energy release. High-speed loading promotes brittle fracture, while low-speed loading enhances energy dissipation. The closer the particle morphology is to a spherical shape, that is, the closer the range of flattening f and elongation e, the more energy is required to break it, and the greater the crushing strength of the particle. Secondly, particle morphology significantly affects the characteristic stress. Irregular spherical particles, that is, those with a flattening f approximately equal to the range of elongation e, require the most energy, can withstand higher loads, and have the highest characteristic stress, making them suitable for use as alternative materials in new road or railway ballast.

[0082] The above examples are merely preferred embodiments of the present invention and are not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, they are not intended to limit the present invention. Therefore, any simple modifications, equivalent variations, and modifications to the above examples that do not depart from the technical solution of the present invention and are based on the technical essence of the present invention shall fall within the scope of protection of the technical solution of the present invention.

Claims

1. A method for detecting the crushing characteristics of single steel slag particles, characterized in that: The following steps are involved: Step S1, screening the steel slag particles to select at least four groups of single steel slag particles according to different particle sizes; Step S2, each group of steel slag single particles of different particle sizes screened in step S1 is further grouped according to different morphologies; Step S3, further refining the steel slag single particles grouped for the second time in step S2, and setting different external loading rates for each group of steel slag single particles after grouping; Step S4: morphologically quantify the slag single particles of each group with different morphologies selected in step S2, selecting three main dimension parameters: the major axis L, the minor axis S, and the intermediate long axis I to determine the relationship between shape, strength, and crushing mode; obtain the external surface shape feature information to obtain a three-dimensional numerical image of each group of particles; Step S5, performing single-particle crushing on each group of steel slag single particles with different shapes and to be subjected to different external loading rates in step S3, and obtaining relevant crushing strength data of the steel slag single particles; Step S6, classifying the crushing modes of the single slag particles crushed in step S5, and analyzing different curve types caused by different morphologies and loading rates; Step S7, deriving the crushing energy of each group of steel slag single particles based on the crushing strength data obtained after the single particle crushing in step S5, where the single particle crushing energy is defined according to the load-displacement curve relationship; Step S8, based on the crushing strength data obtained from the single particle crushing test in step S5, using Weibull distribution statistics, calculate the relationship between the survival probability and characteristic stress of a single slag particle under different shapes and different external loading rates; Step S9: Based on the relationship between the survival probability and the characteristic stress in step S8, further describe the Weibull distribution function of the single particle crushing strength distribution, use its distribution curve to judge the discreteness of the single particle crushing strength, and obtain m and R by fitting. 2 value, m is the Weibull modulus, R 2 is the curve fitting degree.

2. The method for detecting single particle crushing characteristics of steel slag according to claim 1, characterized in that: In step S2, the different forms include at least irregular spherical particles, strip-shaped particles, and flake-shaped particles.

3. The method for detecting single particle crushing characteristics of steel slag according to claim 2, characterized in that: In step S4, the morphology quantification is to calculate the value range of the shape parameters of single slag particles of different shapes through flatness and elongation, and determine the relationship between shape, strength and crushing mode.

4. The method for detecting the crushing characteristics of single steel slag particles according to claim 1, characterized in that: The step S8 specifically includes the following steps: S8-1, Weibull standard expression function is: ； Where, is the crushing strength of single particle of steel slag, is the shape parameter, is the scale parameter; S8-2, Calculate the particle crushing characteristic stress based on the assumption of Weibull statistics The cumulative probability of survival under , that is, the survival probability, is expressed as: ； Where, is the survival probability of the particle, ,in It represents the probability of particle survival, that is, the ratio of the number of unbroken particles to the total number of particles. Indicates the number of unbroken particles, It represents the ratio of the total number of particles; is the particle crushing characteristic stress corresponding to the test load, which is the actual stress value that causes the particle crushing; is the characteristic destructive strength; m represents the Weibull modulus, which characterizes the discreteness of particle strength and is used to measure the dispersion of crushing strength. The larger the m value, the smaller the discreteness of particle strength. S8-3, based on S8-1 and S8-2, the survival probability of a single slag particle under different crushing conditions and the particle crushing characteristic stress can be calculated. relationship.

5. The method for detecting the crushing characteristics of single steel slag particles according to claim 4, characterized in that: In step S9, the Weibull distribution function of the single particle crushing strength distribution is described as follows: The equation for the Weibull modulus m value is obtained by taking the logarithm twice on both sides of the equation for the probability of survival in step S8. The discreteness of the single particle crushing strength is judged by using its distribution curve. Linear regression equation, Represents the particle characteristic stress The modulus m reflects the concentration of the material's probability distribution of breakage. The larger the modulus, the more concentrated the probability distribution of breakage.

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