Method for predicting coke hot strength based on coking coal activity

Abstract

The present application belongs to the technical field of coking coal blending, and particularly relates to a method for predicting coke thermal strength based on coking coal activity, comprising the following steps: S1: determining coking coal activity (H), dry basis ash-free volatile matter (V daf ), and maximum Gieseler fluidity (MF); S2: calculating the logarithm (lgMF) of the maximum Gieseler fluidity (MF); S3: substituting the coking coal activity (H), dry basis ash-free volatile matter (V daf ), and the logarithm (lgMF) of the maximum Gieseler fluidity (MF) into the formula: CRI=9.87+0.134(H)-1.410(lgMF)+0.473(V daf ) and CSR=83.6-0.147(H)+3.390(lgMF)-0.822(V daf ). The method realizes fast coke thermal strength prediction by constructing a mathematical relationship between coking coal activity and coke thermal strength, has high accuracy and strong practicability, can quickly and accurately identify abnormal coking coal quality, avoids passive large-scale adjustment of coal blending structure caused by abnormal coal quality, reduces the imbalance risk between coking coal resource supply and blending, and prevents abnormal rise of coking coal blending cost.

Description

Technical Field

[0001] This invention belongs to the field of coking coal blending technology, and in particular relates to a method for predicting the hot strength of coke based on the activity of coking coal. Background Technology

[0002] With the rapid development of blast furnace ironmaking technology, coke quality, especially its hot strength (reactivity ratio (CRI) and post-reaction strength (CSR), has become a key constraint affecting the stable operation of blast furnaces. Pre-controlling the quality of coking coal and using readily detectable coal quality indicators to predict coke hot strength, thereby achieving stable control of coke hot strength, has become a pressing technical challenge for the coking industry. Currently, coking enterprises generally use small coke oven coking tests for predicting and evaluating coke hot strength. This method is not only time-consuming but also results in delayed application, making it difficult to guide the timely and effective optimization of coking coal blending. Therefore, it is necessary to establish an accurate coke hot strength prediction model to achieve stable control of coke quality.

[0003] Chinese invention patent application number 202010959603X discloses a method for predicting the thermal intensity of coke using a parameter-based comprehensive prediction model. The parameters of this invention include: volatile matter V... daf Adhesion index G, adhesive layer thickness Y, ash content A d The catalytic index was obtained by fitting the alkali metal content in the coal ash, and the coal quality parameter model was obtained by fitting the model through principal component regression analysis. The process operation parameters were measured, and the mathematical model of the process parameter model of the coke heat intensity data change was obtained. Finally, the coke quality prediction model was obtained. Yan Liqiang, Lei Lei, Wang Baorong, et al. Coke quality prediction based on comprehensive coal quality index [J]. Clean Coal Technology, 2021, 27(S2):175-180. This literature selects the V of blended coal. d Fineness, G, b, X, and Y are selected as the six basic indicators for blended coal. d Fineness, G, b, X, Y, R maxThe mechanical strength and hot properties of coke are predicted using KNN and SVR algorithms, with active and inert components as nine-factor comprehensive indicators. All of the above methods for predicting coke hot strength use coal volatile matter (V), caking index (G value), and maximum plastic layer thickness (Y value). These three factors are highly correlated; including them simultaneously in the prediction model can easily lead to overfitting, thus weakening the model's generalization ability. Meanwhile, the Chinese invention patent with application number 202010959603X uses coal ash component indicators. The coke quality prediction method based on comprehensive coal quality indicators uses active and inert component indicators. The testing and analysis of coal ash, active, and inert components all take more than 24 hours, resulting in long prediction cycles and making it difficult to guide the optimization and adjustment of coking coal blending structures in a timely and effective manner.

[0004] Chinese invention patent application number 2025117112356 discloses a method and system for predicting the hot performance of coke based on a 2kg test coke oven. This invention method is based on collecting data on the reactivity and post-reaction strength of coke obtained from coking in a 2kg test coke oven at different times according to actual production ratios, constructing an experimental database, determining the contribution of each type of coal to the post-reaction strength, and calculating the predicted post-reaction strength based on the contribution and ratio of each type of coal in the scheme. This invention patent's method for predicting the hot performance of coke uses a 2kg test coke oven coking test, which usually takes about 22 hours, resulting in a long prediction time and making it impossible to guide the adjustment of coking production ratios in a timely manner. Summary of the Invention

[0005] The purpose of this invention is to provide a method for predicting the hot strength of coke based on the activity of coking coal, thereby solving the problems of overfitting, long prediction cycle, and inability to guide timely adjustment of coking production ratios in existing coke hot strength prediction models.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A method for predicting the hot strength of coke based on the activity of coking coal includes the following steps: S1: The activity (H) and dry basis ash-free volatile matter (V) of coking coal were determined. daf ) and maximum Gibbs free flow (MF); S2: Calculate the logarithm (lgMF) of the maximum Gibbs free flow (MF); S3: The activity (H) and volatile matter (V) of coking coal on a dry basis and without ash on a dry basis. daf Substituting the logarithm (lgMF) of the maximum Gibbs free flow (MF) into the formula: CRI=9.87+0.134(H)-1.410(lgMF)+0.473(V daf ), CSR=83.6-0.147(H)+3.390(lgMF)-0.822(V daf In the formula: CRI: predicted reactivity of coke obtained from coking coal smelting, %; CSR: predicted post-reaction strength of coke obtained from coking coal smelting, %; H: coking coal activity, %; V daf : Dry basis ash-free volatile matter of coking coal, %; lgMF: Logarithm of the maximum Gibbs free flowability (MF) of coking coal (lgMF), used to predict the reactivity CRI and post-reaction strength CSR of coke obtained from coking coal smelting.

[0007] Preferably, the range of coking coal activity (H) in step S1 is 18%-83%.

[0008] Preferably, the coking coal in step S1 is a single type of coal used for metallurgical coke smelting or a blended coal composed of various single types of coal in a certain proportion.

[0009] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: (1) By detecting the activity index of coking coal, the hot strength of coke (reactivity CRI and post-reaction strength CSR) can be predicted quickly and accurately. The prediction time is short and the prediction deviation is within ±1%. The accuracy is high, which enables rapid response and guidance to the coking coal blending scheme, stabilizes the hot strength of coke, and provides a reliable raw material guarantee for the stable operation of the blast furnace. (2) By constructing a mathematical relationship between the activity of coking coal and the hot strength of coke (reactivity CRI and post-reaction strength CSR), the hot strength of coke can be predicted quickly and accurately. It is highly accurate and practical, and can quickly and accurately identify abnormalities in the quality of coking coal, avoid the passive and significant adjustment of the coal blending structure caused by abnormal coal quality, reduce the risk of imbalance between the supply and use of coking coal resources, and prevent abnormal increases in the cost of coking coal blending. Detailed Implementation

[0010] The technical solution of the present invention will be described in detail below with reference to the embodiments.

[0011] Unless otherwise stated, the technical and scientific terms used in this invention have the same meanings as commonly understood by one of ordinary skill in the art to which this invention pertains. For example, the following references provide basic guidance for those skilled in the art regarding the technical terms used in this invention: Yao Zhaozhang, Zheng Mingdong, *Coking Science*, 3rd edition, Metallurgical Industry Press, 2010; He Xuanming, *Coal Chemistry*, Metallurgical Industry Press, 2nd edition, 2010; Pan Lihui, *Q&A on Coking Technology*, Metallurgical Industry Press, 2013; Xu Zhengang, *Clean Coal Technology in China*, Coal Industry Press, 2012; Ma Shichang, *Dictionary of Chemical Substances*, Shaanxi Science and Technology Press, 1999; Lin Cong, *Encyclopedia of Chinese Metallurgy*, Metallurgical Industry Press, 1998; Chen Peng, *Properties, Classification and Utilization of Chinese Coal*, 2nd edition, Chemical Industry Press, 2018; *Chinese Coal Classification Standard GB / T 5751-2009*.

[0012] A method for predicting the hot strength of coke based on the activity of coking coal includes the following steps: S1: Determine the volatile matter V of single coal or blended coal according to GB / T 212-2008 "Industrial Analysis Methods for Coal". daf The maximum Gibbs flowability MF of a single type of coal or a blended coal was determined according to GB / T 25213-2010 "Determination of Plasticity of Coal by Constant Torque Gibbs Plastic Instrument Method"; the activity H of a single type of coal or a blended coal was determined according to GB / T 220-2018 "Determination of Chemical Reactivity of Coal to Carbon Dioxide" (the determination process is as follows: a coal sample is weighed and placed in the sample tube of the reactor, heated to 1050℃ to produce coke, cooled and weighed, the mass of the coke m1 is then measured, the coke is returned to the sample tube of the reactor, the reaction gas CO2 is introduced, the temperature is kept constant for 2 hours, cooled, and the mass of the coke m2 is measured again, and the coking coal activity is calculated as (m1-m2) / m1×100%). S2: Calculate the logarithm lgMF of the maximum Gibbs free flowability MF; S3: Then measure the dry basis (ash-free) of the single coal or blended coal. daf Substituting the activity H, the logarithm of the calculated maximum Gibbs free flow rate MF (lgMF) into the formula: CRI=9.87+0.134(H)-1.410(lgMF)+0.473(V daf ), CSR=83.6-0.147(H)-0.822(V daf ) +3.390 (lgMF), The reactivity CRI and post-reaction strength CSR of coke obtained by coking with this single type of coal or blended coal are predicted.

[0013] In the following examples, a 40kg bottom-charged test coke oven was used for single-coal coking. The initial temperature of the 40kg test coke oven was 800℃, the final temperature was 1050℃, and the coking time was 17h. It was used in conjunction with a 7.63m industrial coke oven for coal coking. The furnace temperature of the 7.63m industrial coke oven was 1321-1328℃, and the coking time was 26.5h.

[0014] The dry basis ash-free volatile matter V of No. 1 coking coal, No. 1 fat coal, No. 1 1 / 3 coking coal, No. 1 lean coal and No. 1 gas coal were determined respectively. daf The activity H and maximum Gibbs free flowability MF were calculated, and the logarithm lgMF of the maximum Gibbs free flowability MF was calculated. The dry basis ash-free V values ​​of No. 1 coking coal, No. 1 fat coal, No. 1 1 / 3 coking coal, No. 1 lean coal, and No. 1 gas coal were respectively calculated. daf Substituting the logarithm of activity H and maximum Gibbs free flow MF into the prediction formula of the method of the present invention, the predicted values ​​of reactivity CRI and post-reaction strength CSR of coke obtained from the coking of the above five single coals are obtained. The specific results are listed in Table 1.

[0015] Single-coke coking tests were conducted in a 40kg test coke oven using No. 1 coking coal, No. 1 fat coal, No. 1 1 / 3 coking coal, No. 1 lean coal, and No. 1 gas coal, respectively. According to GB / T 4000-2017 "Methods for Determination of Coke Reactivity and Post-Reaction Strength", the measured values ​​of coke reactivity (CRI) and post-reaction strength (CSR) obtained from coking with the five single coals were determined. The specific results are listed in Table 1.

[0016] Table 1. Measured and predicted values ​​of hot coke strength obtained from coking with five types of single coal.

[0017] The average deviation between the measured and predicted values ​​of the coke reactivity CRI and post-reaction strength CSR obtained from the coking of the five single coals in Examples 1-5 was 1.0%, indicating that the prediction method for the hot strength of coke in this invention has high accuracy and small prediction error.

[0018] Six coal blending schemes used in the industrial production of a 7.63m coke oven were selected to predict the hot strength of coke. The specific coal blending schemes are listed in Table 2. The dry basis ash-free volatile matter V of the blended coal was measured for each of the above coal blending schemes. daf The activity H and maximum Gibbs free flowability MF were calculated, and the logarithm lgMF of the maximum Gibbs free flowability MF was calculated; the dry basis ash-free volatile matter V of the above five blended coals were respectively... daf Substituting the logarithm of activity H and maximum Gibbs free flow MF into the prediction formula of the present invention, the predicted values ​​of coke reactivity CRI and post-reaction strength CSR obtained from the coking of the above 5 blended coals are obtained. The specific results are listed in Table 3. The measured values ​​of hot strength of coke produced from the above 5 blended coals are also listed in Table 3.

[0019] Table 2 Coal blending scheme for 7.63m coke oven

[0020] Table 3. Measured and predicted values ​​of hot strength of coke from a 7.63m coke oven.

[0021] The comparison results of the coke hot-state intensity of the above-mentioned experimental coke oven and industrial coke oven show that the deviation between the predicted value and the measured value obtained by the coke hot-state intensity prediction method of the present invention is small, which verifies that the method of the present invention has good prediction accuracy and universality. Moreover, the entire process of each embodiment takes less than 6 hours, and the prediction cycle is short. Applying the method of the present invention to predict and judge the coke hot-state intensity can realize timely and effective adjustment of the coking coal blending structure, stabilize the coke hot-state intensity, and prevent abnormal increase in coking coal blending costs.

[0022] The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present invention, various simple modifications can be made to the technical solution of the present invention, and these simple modifications all fall within the protection scope of the present invention.

Claims

1. A method for predicting the hot strength of coke based on the activity of coking coal, characterized in that, Includes the following steps: S1: The activity (H) and dry basis ash-free volatile matter (V) of coking coal were determined. daf ) and maximum Gibbs free flow (MF); S2: Calculate the logarithm (lgMF) of the maximum Gibbs free flow (MF); S3: The activity (H) and volatile matter (V) of coking coal on a dry basis and without ash on a dry basis. daf Substituting the logarithm (lgMF) of the maximum Gibbs free flow (MF) into the formula: CRI=9.87+0.134(H)-1.410(lgMF)+0.473(V daf ) CSR=83.6-0.147(H)+3.390(lgMF)-0.822(V daf In the formula: CRI: predicted reactivity of coke obtained from coking coal smelting, %; CSR: predicted post-reaction strength of coke obtained from coking coal smelting, %; H: coking coal activity, %; V daf : Dry basis ash-free volatile matter of coking coal, %; lgMF: Logarithm of the maximum Gibbs free flowability (MF) of coking coal (lgMF), used to predict the reactivity CRI and post-reaction strength CSR of coke obtained from coking coal smelting.

2. The method for predicting the hot strength of coke based on the activity of coking coal according to claim 1, characterized in that, The range of coking coal activity (H) in step S1 is 18%-83%.

3. The method for predicting the hot strength of coke based on the activity of coking coal according to claim 1, characterized in that, In step S1, the coking coal is a single type of coal used for metallurgical coke smelting or a blended coal composed of various single types of coal in a certain proportion.

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