Predicating method for abrasive resistance of coal-blending coking coke

Abstract

The invention discloses a predicating method for abrasive resistance of coal-blending coking coke. The predicating method comprises the following steps: (1) measuring an ash composition, a coke-forming optical tissue structure and a vitrinite mean maximum reflectance of each single coal for coking, calculating or counting the following indexes: a coal-blending mineral substance index MCI, sum N of content of a coarse-grain inlaying component, a medium-grain inlaying component and an incomplete fiber component in the coal blending, sum N of contents of an isotropous component and a fine-grain inlaying component, proportion P of lean coals with reflectance Rmax larger than and equal to 1.65 in themixed coal; (2) setting M10=A+B*MCI+C*M+E*N+F*P, wherein M10 is the abrasive resistance of the coke, unit being %; A, B, C, E and F are constants; and (3) calculating to obtain the predicated abrasive resistance value M10 of the coke. According to the predicating method disclosed by the invention, through few influence factors and simple predicating formulas, the abrasive resistance of the coke can be predicated very well under the condition without coal-blending coking test, so that the predication precision can be within + / -0.3%, and the coke-blending practice can be guided very well.

Description

technical field [0001] The invention belongs to the technical field of metallurgy and coking, and in particular relates to a method for predicting the abrasion resistance strength of coal blending and coking coke. Background technique [0002] Coke is an irregular porous body containing cracks and defects mainly composed of carbon. The number of microcracks in the coke block and the porosity structure of the coke body are closely related to the wear resistance and high temperature response performance of coke. The porospore structure is usually expressed by parameters such as porosity, average diameter of pores, pore size distribution, thickness of pores wall and specific surface area. [0003] At present, the prediction methods of coke wear resistance mainly include: [0004] 1) Through functions such as regress and robustfit in the MATLAB environment, various indicators of coking blend coal such as ash (A d ), volatile matter (V daf ), cohesion index (G) and colloidal ...

AI Technical Summary

Problems solved by technology

[0005] This prediction method has the following deficiencies: ① As a solid material, coke’s physical and chemical properties are closely related to its micro-optical structure. The volatile matter (V daf ), cohesion index (G) and colloidal layer thickness (Y) are the indicators of apparent process properties, which do not take into account the coking optical structure of each single coal involved in coking, which has limitations

The disadvantage of this method is that the test workload is large and the cycle is long

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