Method for predicting mechanical strength and thermal properties of coke

A technology of mechanical strength and thermal properties, applied in the field of coal chemical industry, can solve problems such as inaccurate prediction of coal quality indicators, and achieve the effects of overcoming inaccurate prediction of coke quality, reducing coal blending costs, and accurate prediction

Active Publication Date: 2010-03-03
SINOSTEEL ANSHAN RES INST OF THERMO ENERGY CO LTD
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Problems solved by technology

[0007] The purpose of this invention is to provide a method for predicting the mechanical strength and thermal properties of coke. This method has been proved by a large number of experiments. The vitrinite reflectance distribution of coal is used as the main input parameter of the coal quality index, combined with BP neural network or calculation method to predict Coke index, which overcomes the above-mentioned shortcomings of inaccurate coal quality index prediction

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  • Method for predicting mechanical strength and thermal properties of coke
  • Method for predicting mechanical strength and thermal properties of coke
  • Method for predicting mechanical strength and thermal properties of coke

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[0045] A method for predicting the mechanical strength and thermal properties of coke. The method uses the reflectance distribution of vitrinite as the main input parameter to predict the mechanical strength index and thermal property index of coke.

[0046] 1. Prediction of coke mechanical strength index is realized through BP neural network; coke mechanical strength index includes crushing strength (M 40 ) and abrasion resistance (M 10 ), which is related to the metamorphic degree and caking property of coal. The present invention uses vitrinite reflectance distribution and cohesiveness index (such as cohesive index G, colloidal layer maximum thickness Y) as parameters, and predicts coke mechanical strength through BP neural network.

[0047] The vitrinite reflectance of a large number of representative coals in the historical production data is divided into six segments (A, B, C, D, E, F) (see Appendix 1 for the division method of vitrinite reflectance). The cohesiveness ...

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Abstract

The invention relates to a method for predicting the mechanical strength and thermal properties of coke. In the method, vitrinite reflectance distribution of coal is used as a main input parameter to predict the mechanical strength and thermal property indexes of the coke. The prediction of the mechanism strength index of the coke is realized by a BP neural network, and the prediction of the thermal property index is realized by the BP neural network or a calculation method. The method can ensure the effective use of coke coal resources, scientifically and accurately predict the cold strengthand thermal property of the coke, guarantee the quality of the coke, reduce coal blending cost, realize scientific coal blending and implement a coal blending expert system.

Description

technical field [0001] The invention relates to the technical field of coal chemical industry, in particular to a method for coal blending coking and coke quality control and prediction in coking production. Background technique [0002] In recent years, China's coke production capacity has expanded rapidly, the supply of coking coal resources is tight, scarce high-quality coking coal resources are becoming less and less, the coal sources of coking plants fluctuate frequently, the coal quality fluctuates greatly, and the situation of mixed coal is serious; with the large-scale blast furnace , The improvement of coal injection technology requires higher and higher coke quality. In order to stabilize the quality of coke, it is an important subject for the coking industry to carry out coke quality prediction research. [0003] The early coking coal blending ratio at home and abroad was tested in the laboratory by trial and error method based on experience and coal quality para...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N33/00
Inventor 孟庆波战丽刘洋
Owner SINOSTEEL ANSHAN RES INST OF THERMO ENERGY CO LTD
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