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Method for establishing metallurgical coke pore feature parameter prediction model

A technology of characteristic parameters and prediction model, applied in the field of coking, can solve the problem of unpredictable pore structure parameters, and achieve the effect of simple test and high accuracy

Active Publication Date: 2017-03-29
NORTH CHINA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Problems solved by technology

Although this method optimizes the coal blending scheme and achieves a certain coke quality control effect, it cannot predict the pore structure parameters after coking according to the characteristics of the specific blended coal.

Method used

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  • Method for establishing metallurgical coke pore feature parameter prediction model
  • Method for establishing metallurgical coke pore feature parameter prediction model

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Embodiment Construction

[0017] (1) A total of 18 samples of single coal and its blending coals of different coal ranks were selected, and the samples were subjected to thermogravimetric analysis with a thermal analyzer. The sample size (air-dried coal sample) was 10.0 mg, from 30°C. The temperature is increased to 950°C at a temperature rise rate of 3°C / min, and the argon flow rate is 60ml / min. According to the thermogravimetric test curve, the volatilization of each sample is analyzed to obtain the maximum rate DTG max (% / minute);

[0018] (2) Using a Gee's fluidity tester, measure the Gee's fluidity of 18 samples in accordance with GB / T 25213-2010, and obtain the Gee's maximum fluidity MF (division / min) of each sample;

[0019] (3) The coking coal sample is subjected to a coking experiment to obtain a coke sample, and the pore parameters of the coke are detected by image analysis, including the average pore size, porosity, ratio of pores less than 30 microns and ratio of pores greater than 150 microns. ...

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Abstract

The invention discloses a method for establishing a metallurgical coke pore feature parameter prediction model. The method is characterized by comprising the steps of: 1) performing thermo-gravimetric analysis test on a single coal of more than 15 different coal ranks and a matching coal thereof to obtain a maximum volatile de-volatilization rate DTGmax (% / min) of each sample; 2) performing Gieseler fluidity test on a coking coal to obtain a maximum Gieseler fluidity MF (graduation / min) of each sample; 3) performing coking test on the coking coal samples, and obtaining the average pore size, porosity, proportion of pores smaller than 30 microns and proportion of pores greater than 150 microns of coke via an image analysis method; and 4) performing binary linear regression on the average pore size, porosity, proportion of pores smaller than 30 microns and proportion of pores greater than 150 microns of the coke respectively by using DTGmax and LgMF as independent variables to obtain a relation between the pore structure parameters and the DTGmax and LgMF. The prediction method is simple and convenient in test and high in prediction accuracy.

Description

Technical field [0001] The invention belongs to the technical field of coking, and particularly relates to the prediction of pore characteristics of coke for blast furnace. [0002] technical background [0003] Coke is an indispensable raw material for blast furnace smelting, and its performance directly affects the gas permeability, liquid permeability and other conditions in the furnace. The coke bears the mechanical load in the furnace and resists various physical damage and chemical attack. Therefore, the coke is required to have sufficient strength. The pore structure has a crucial influence on coke performance. The porosity of coke and the distribution of different levels of pores will also affect the cold strength of coke. In addition, the pore structure of the coke will also affect the diffusion of the reaction gas into the coke, thereby affecting the gasification reactivity of the coke. The increase in the porosity and average pore diameter of the coke makes the carbon...

Claims

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Application Information

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IPC IPC(8): G06F17/50
Inventor 梁英华郭瑞胡文佳王杰平孙章
Owner NORTH CHINA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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