A method for predicting the proportion of weakly caking coal in stamped coke

Abstract

The present invention relates to the field of blast furnace fuel quality control and efficient utilization in the field of metallurgical production, and specifically to a method for predicting the proportion of weakly caking coal in stamped coke. The method comprises the following steps: 1) sample preparation: randomly selecting N samples, where N is greater than or equal to 7; 2) X-ray diffraction measurement: performing XRD analysis on the N samples obtained in step 1) to obtain X-ray diffraction spectra; 3) data peak decomposition: performing peak decomposition on the XRD spectra obtained in step 2) to obtain the XRD diffraction peak 002; 4) characterization of the coke microstructure: quantitatively characterizing the microstructure using the microstructure parameter d002, where d002 is the distance between single aromatic layers of the coke microstructure; and 5) statistical calculation: calculating the d002 data of each sample, and calculating its average value E and standard deviation σ, which are used to predict and determine the proportion of weakly caking coal in stamped coke. The method provides guidance to steel companies in selecting and purchasing stamped coke according to their needs based on the above aspects.

Description

Technical Field

[0001] The present invention relates to the field of blast furnace fuel quality control and efficient utilization in the field of metallurgical production, and in particular to a method for predicting the proportion of weakly caking coal in ramming coke. Background Art

[0002] Traditional top-charging coking processes hinder cost reduction for steelmakers and pose a significant obstacle to the sustainable development of the ironmaking industry. Stamped coke offers advantages such as a wide range of material selection, significantly improved coke quality, high coke production capacity, and superior environmental performance. It is highly compatible with my country's coking coal resources and has received support from both national policies and businesses.

[0003] However, due to the differences in the production processes of rammed coke and top-charged coke, there are significant differences in the performance of the two types of coke, and the commonly used indicators and microstructure are quite different from those of top-charged coke. Studies have shown that some companies have too high a proportion of weakly caking coal, and simply rely on the ramming process to increase the pressure, which causes large horizontal closed air holes to appear between the coke layers, affecting actual use. Coal blending is the most important factor determining the quality of coke, and the ramming process can improve the cold strength and hot properties to a certain extent, and has a certain effect on the porosity of coke. With the increase in the proportion of coking coal, the cold strength and hot properties of coke are improved to varying degrees. Among them, ramming coking has a significant effect on the cold strength and hot strength index of coke, and the effect of the ramming coking process on the improvement of coke strength gradually weakens with the increase of the proportion of coking coal. Some companies have too high a proportion of weakly caking coal, and simply rely on the ramming process to increase the pressure, which causes large horizontal closed air holes to appear between the coke layers, affecting actual use. Since the microstructures of different types of coke are not very different, the microstructure and properties of stamped coke are greatly affected by the coal blending structure. Therefore, the coal blending structure of stamped coking should not differ too much from that of top-charging coking.

[0004] However, in the process of using rammed coke in large blast furnaces, it was found that the thermal performance indicators of some coke were poor, which was closely related to the addition of more weakly caking coal. Steel companies urgently need to find a method to predict the coal blending structure of purchased coke. Summary of the Invention

[0005] Iron and steel enterprises lack effective prediction methods for the coal blending structure adopted by purchased rammed coke, resulting in large differences in the adaptability of different types of rammed coke during blast furnace application, which often causes fluctuations in blast furnace indicators. The present invention provides a method for predicting the proportion of weakly caking coal in rammed coke, a method for predicting the proportion of weakly caking coal in rammed coke by multiple measurements of X-ray diffraction. The method includes the steps of sample preparation, X-ray diffraction measurement of multiple samples, data peak decomposition and calculation, statistically obtaining the standard deviation of multiple samples, and looking up a table to predict the weakly caking proportion. The basic principle is: as the proportion of weakly caking coal in the properties of mother coking coal (such as coal rank and lithologic composition) increases, the microcrystalline interlayer spacing d002 will deviate from the main coking coal interval, thereby affecting the degree of microcrystallization, reactivity and post-reaction strength of the coke. Therefore, judging the d002 parameter is the main step in predicting the coal blending structure. Coking raw materials are made by mixing raw coal of a certain particle size, and their X-ray diffraction results are usually an overall reflection of the diffraction structure of coke after carbonization of different types of coal. To achieve better coke properties in both hot and cold states, top-charged coke typically uses a lower weakly caking ratio. Consequently, the main coking coal has a greater influence on X-ray diffraction analysis, resulting in minimal differences in the characteristic parameter d002 across multiple locations, and also relatively low differences between different top-charged cokes. However, because the tamping process uses a higher proportion of weakly caking coals, such as weakly caking coal, gas coal, lean coal, and anthracite, this leads to greater fluctuations in the characteristic parameter d002 across different samples, and also greater differences in d002 across multiple locations for the same sample. By analyzing X-ray diffraction results from multiple locations for various top-charged and tamped coke samples, the ranges and deviations of the d002 characteristic parameters for both types of coke were determined. Regression relationships were used to determine the proportion of the main coking coal used in the tamping coke blending process, and thus to infer the proportion of weakly caking coal.

[0006] To achieve the above object, the present invention provides a method for predicting the proportion of weakly caking coal in stamped coke, comprising the following steps:

[0007] 1) Sample preparation: randomly select N samples, N ≥ 7;

[0008] 2) X-ray diffraction measurement: performing XRD analysis on the N samples obtained in step 1) to obtain X-ray diffraction spectra;

[0009] 3) Data peak decomposition: The XRD spectrum obtained in step 2) is decomposed to obtain the XRD diffraction peak 002;

[0010] 4) Characterization of the microstructure of coke: by the microstructure parameter d 002 Quantitative characterization, where d 002 is the distance between the monolayers of aromatic layers in the coke crystal structure;

[0011] 5) Statistical calculation: Calculate the d of each sample002 The data are used to calculate the average value E and standard deviation σ, which are used to predict the proportion of weakly caking coal in ramming coke.

[0012] Preferably, the randomly selected sample in step 1) is coke particles having a size of (10 mm ± 3 mm)*(10 mm ± 3 mm).

[0013] The present invention provides a method for predicting the proportion of weakly caking coal in the coal blending structure of stamped coke. The experimental steps include sample preparation, X-ray diffraction measurement, data peak decomposition and calculation, and table lookup to predict the weakly caking ratio. The specific steps are as follows:

[0014] 1) Sample preparation. Use a jaw crusher and a roller crusher to crush the rammed coke into granular coke with a particle size of about 10 mm. Randomly select 7 samples with relatively flat surfaces. Coke particles with a surface size of 10 mm*10 mm (±1 mm) are selected as the sample and ground with sandpaper to a relatively flat surface.

[0015] 2) XRD analysis was performed on seven coke samples. X-ray diffractometer measurements were performed using a Cu target as the X-ray source. X-ray diffraction patterns were obtained by scanning over a 2θ range of 10–70° at a step rate of 3° / min.

[0016] 3) Peak decomposition. Peak decomposition of XRD spectrum is performed as follows: Figure 1 The fitted peaks are all Gaussian peaks. The 2θ peak of about 26° in the XRD spectrum shown in the figure corresponds to the graphite 002 peak.

[0017] (4) The degree of ordering of the microstructure of coke is determined by the microstructure parameter d 002 To quantitatively characterize (where d 002 is the distance between the aromatic layers of the coke microcrystal structure), calculated using formula (1)

[0018]

[0019] Where λ = 0.15406 nm, which is the incident wavelength.

[0020] (5) Statistical calculation of d for each sample 002 Data, calculate its mean E and standard deviation σ;

[0021] (6) The proportion of weakly caking coal in the production process of ramming coke blending is obtained by looking up Table 1. The deviation between the predicted value and the actual value is within 9%.

[0022] Table 1 Corresponding relationship between the standard deviation σ of d002 and the proportion of weakly caking coal

[0023]

[0024] Compared with the prior art, the advantages of the present invention are:

[0025] According to this method, the proportion of weakly caking coal in ramming coal blending can be predicted and determined, and the steel enterprises can be guided to purchase ramming coke according to their needs from the above aspects. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 Schematic diagram of the fitting curve of the γ peak and 002 peak of the XRD spectrum of the present invention. DETAILED DESCRIPTION

[0027] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments.

[0028] (1) Sample preparation. A jaw crusher and a roller crusher were used to crush the rammed coke into granular coke with a particle size of about 10 mm. Seven samples with relatively flat surfaces were randomly selected. Coke particles with a surface size of 10 mm*10 mm (±1 mm) were selected as the sample and ground into a relatively flat surface using sandpaper.

[0029] (2) XRD analysis was performed on seven coke samples. X-ray diffractometer was used for measurement. A Cu target was used as the X-ray source, and the X-ray diffraction patterns were obtained by scanning in the 2θ range of 10–70° at a step rate of 3° / min.

[0030] (3) Peak decomposition. Peak decomposition of XRD spectrum is performed according to the method shown in Figure 1 The fitted peaks are all Gaussian peaks. The 2θ value of about 26° in the XRD spectrum shown in the figure corresponds to the graphite 002 peak;

[0031] (4) The degree of ordering of the microstructure of coke is determined by the microstructure parameter d 002 To quantitatively characterize (where d 002 is the distance between the monolayers of aromatic layers in the coke microcrystal structure);

[0032] (5) Statistical calculation of d for each sample 002 The data were used to calculate the mean value E to be 0.35222 and the standard deviation σ to be 0.00174 nm.

[0033] (6) The proportion of weakly caking coal in the production process of ramming coke blending is obtained by looking up Table 1. The deviation between the predicted value and the actual value is within 9%.

[0034] According to this method, the proportion of weakly caking coal in ramming coal blending can be determined, and the above aspects can be used to guide steel companies in purchasing ramming coke according to their needs.

[0035] Example:

[0036] For a company purchasing ramming coke, the proportion of weakly caking coal to be added is predicted.

[0037] (1) Sample preparation. For a type of rammed coke purchased from an enterprise, a jaw crusher and a roller crusher were used to crush the rammed coke into granular coke with a particle size of about 10 mm. Seven samples with relatively flat surfaces were randomly selected, and coke particles with a surface size of 11 mm*10 mm were selected as the objects. The coke particles were ground into a relatively flat surface using sandpaper.

[0038] (2) XRD analysis was performed on seven coke samples. X-ray diffractometer was used for measurement. A Cu target was used as the X-ray source, and the X-ray diffraction patterns were obtained by scanning in the 2θ range of 10–70° at a step rate of 3° / min.

[0039] (3) Peak decomposition. Peak decomposition of XRD spectrum is performed according to the method shown in Figure 1 , the fitted peak shapes are all Gaussian peaks;

[0040] (4) The degree of ordering of the microstructure of coke is determined by the microstructure parameter d 002 to quantitatively characterize (where d002 is the distance between the aromatic monolayers of the coke microcrystal structure);

[0041] (5) Statistical calculation of d for each sample 002 The data were used to calculate the mean value E to be 0.35222 and the standard deviation σ to be 0.00174 nm.

[0042] (6) According to Table 1, the proportion of weakly caking coal in the production process of ramming coke blending is in the range of 28-35%. According to the coking enterprise, the proportion of weakly caking coal in this batch of ramming coke blending is 29%. This shows that the prediction of this method is relatively accurate.

[0043] This method can be used to determine the proportion of weakly caking coal in the tamping coal blend, and can guide steel companies in selecting tamping coke based on their needs. Based on this, it is determined that the incorporation of low-caking coal in the tamping coke production process is appropriate, and that the improved high-temperature thermal properties are achieved without sacrificing the proportion of primary coking coal. It is expected that, while meeting current blast furnace coke charging specifications, this will not adversely affect blast furnace production.

[0044] Any content not described in detail in the present invention can be based on conventional technical knowledge in the art.

[0045] Finally, it should be noted that the above embodiments are intended only to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention and are intended to be encompassed by the claims of the present invention.

Claims

1. A method for predicting the proportion of weakly caking coal in stamped coke, comprising the following steps: 1) Sample preparation: randomly select N samples, N ≥ 7; 2) X-ray diffraction measurement: performing XRD analysis on the N samples obtained in step 1) to obtain X-ray diffraction spectra; 3) Data peak decomposition: The XRD spectrum obtained in step 2) is decomposed to obtain the XRD diffraction peak 002; 4) Characterization of the microstructure of coke: by the microstructure parameter d 002 Quantitative characterization, where d 002 is the distance between the monolayers of aromatic layers in the coke crystal structure; 5) Statistical calculation: Calculate the d of each sample 002 The data are used to calculate the average value E and standard deviation σ, which are used to predict the proportion of weakly caking coal in ramming coke. In the step 5), d 002 When the standard deviation σ is greater than 0.0022 nm, the proportion of weakly caking coal in the ramming coke is predicted to be greater than 35%. d 002 When the standard deviation σ value range is 0.0022-0.0015nm, the weakly caking coal ratio in the ramming coke is predicted to be 28-35%; d 002 When the standard deviation σ is in the range of 0.0015-0.0010 nm, the weakly caking coal ratio in the ramming coke is predicted to be 22-28%. d 002 When the standard deviation σ is less than 0.0010 nm nm, it is predicted that the proportion of weakly caking coal in the ramming coke is less than 22%.

2. The method according to claim 1, characterized in that The randomly selected samples in step 1) are coke particles with a size of (10 mm ± 3 mm) * (10 mm ± 3 mm).

3. The method according to claim 1, characterized in that The XRD spectrum in step 3) corresponds to the graphite 002 peak.

4. The method according to claim 1, wherein In the step 4), d 002 The calculation formula is: Wherein, λ is the incident wavelength, λ = 0.15406 nm.

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