CN-121972283-A - Coking coal preparation method for improving selectivity of extremely difficult coal dressing by washing

CN121972283ACN 121972283 ACN121972283 ACN 121972283ACN-121972283-A

Abstract

The invention discloses a coking coal preparation method for improving the selectivity of extremely difficult coal dressing by blending and washing, and belongs to the technical field of coal washing and selecting processing. The method comprises the steps of firstly carrying out a floating and sinking test on target extremely difficult coal, generating a continuous density-yield distribution function, quantitatively screening compatible coal types which are complementary with the target coal in a separation key density interval by taking a density distribution complementarity index as a compatibility criterion, determining an optimal ratio for maximizing the yield of target ash under the constraint of coking performance of the caking index of the clean coal not lower than 80 and the thickness of a colloid layer not lower than 16.5mm, and sending the mixed coal into a dense medium cyclone for separation, and synchronously optimizing the stability of suspension and a slime water system. The method obviously improves the overall density distribution curve of the mixed raw coal, improves the yield of the clean coal by 12 to 18 percent, finally produces qualified coking clean coal, and realizes the conversion of extremely difficult clean coal from low-value power coal to high-value coking coal.

Inventors

JIN PENG
LI LONG
LIU WENJU
Dang dan
XING BAOLIN
HU YANSHAO
ZHANG JING
DING MINGJIE
GAO JIANWEI
LV BO
WANG TIANYUAN
HAN QUNLIANG
YANG SHUJIA
Peng Shuaihu
WANG XINGSHENG
ZHOU YUEHUI
XING NING
WANG SONGLIN
HU JIYONG
WANG XUFENG
ZHU GAOHUI

Assignees

中国平煤神马控股集团有限公司
河南科技学院
河南城建学院
河南工业大学
河南理工大学
河南平煤神马京宝化工科技股份有限公司
平顶山天安煤业股份有限公司

Dates

Publication Date: 20260505
Application Date: 20260320

Claims (10)

1. The coking coal preparation method for improving the selectivity of extremely difficult coal dressing by blending and washing is characterized by comprising the following steps of: s1, carrying out a floating and sinking test on target extremely difficult coal according to at least six standard density levels, obtaining yield and ash data of each density level, generating a continuous density-yield distribution function and a density-ash relation curve through interpolation fitting, and calculating the single-coal theoretical clean coal yield under target ash; S2, respectively executing a sink test on a plurality of candidate coal types, acquiring respective density-yield distribution functions, and calculating a density distribution complementarity index between each candidate coal type and target extremely difficult coal, wherein the density distribution complementarity index is used for quantitatively representing the complementarity degree of density distribution defects of target coal and candidate coal types in a separation key density interval, and selecting candidate coal types with the density distribution complementarity index meeting a preset threshold as compatible coal types; s3, carrying out weighted superposition on a density-yield distribution function of the target extremely difficult coal and a density-yield distribution function of the compatible coal types according to different proportions to generate a plurality of groups of mixed coal theoretical optional curves, and determining an optimal proportion for maximizing the theoretical yield of the clean coal under the target ash under the coking performance constraint that the clean coal bonding index is not lower than 80 and the colloid layer thickness is not lower than 16.5 mm and the quality constraint that the clean coal ash does not exceed the target ash value; s4, mixing the target extremely difficult coal with the compatible coal types according to the optimal ratio, and sending the mixed raw coal into a dense medium cyclone for density separation, wherein the separation density is set according to a separation density value corresponding to the target ash on a mixed coal theoretical selectivity curve, so that the coking clean coal meeting the target ash requirement is obtained.
2. The coking coal preparation method for improving the selectivity of extremely difficult coal dressing by proportioning and washing according to claim 1, wherein in the step S2, the separation key density interval is 1.3g/cm 3 to 1.6g/cm 3 , and the density distribution complementarity index is calculated in the following manner: Respectively obtaining a first deviation function between a density-yield distribution function of the target extremely difficult coal and a preset ideal selectivity distribution function and a second deviation function between a density-yield distribution function of the candidate coal and the ideal selectivity distribution function; Performing integral operation on the product of the first deviation function and the second deviation function in the sorting key density interval to obtain a deviation cooperative integral value, and performing integral operation on the square of the larger one of the first deviation function and the second deviation function to obtain a deviation reference integral value; Normalizing the ratio of the deviation cooperative integral value to the deviation reference integral value to obtain a density distribution complementarity index; The ideal selectable distribution function is a standard distribution function with the low density level yield ratio higher than a preset first proportion threshold value and the intermediate density level yield ratio lower than a preset second proportion threshold value in a sorting key density interval.
3. The method for preparing coking coal for improving the selectivity of extremely difficult coal preparation by proportioning and washing according to claim 1, wherein the step S2 further comprises the step of evaluating the compatibility of the surface properties of candidate coal types: measuring the contact angle and Zeta potential of the target extremely difficult coal and each candidate coal; Calculating the absolute value of the contact angle difference value and the absolute value of the Zeta potential difference value between the target extremely difficult coal and each candidate coal; judging the candidate coal types with contact angle difference absolute values not exceeding 15 degrees and Zeta potential difference absolute values not exceeding 10mV as surface property compatible coal types; And determining the candidate coal types meeting the density distribution complementarity index threshold and the surface property compatibility condition at the same time as the final compatible coal types.
4. The method for preparing coking coal for washing to improve the selectivity of extremely difficult coal according to claim 1, wherein the step S3 further comprises: the mass ratio of the target extremely difficult coal to the mixed coal is not lower than 50 percent, which is the lower limit constraint of the proportion; the mixed coal is selected from the group consisting of coal and coal, wherein the near-heavy matter content of the mixed coal in the range of the sorting density of plus or minus 0.1g/cm 3 is not more than 40 percent; establishing a multi-objective optimization model by taking the theoretical yield and the economic value of the clean coal as double objectives; the method comprises the steps of obtaining a Pareto optimal proportioning set by carrying out system search in a proportioning space meeting proportion lower limit constraint, selectivity constraint, coking performance constraint and quality constraint, and selecting a proportioning scheme taking yield and economy into consideration from the Pareto optimal proportioning set as optimal proportioning.
5. The coking coal preparation method for improving the selectivity of extremely difficult coal dressing by blending and washing according to claim 1, wherein the coking coal caking index G value and the colloid layer thickness Y value in the coking performance constraint in the step S3 are obtained through a nonlinear prediction model, the nonlinear prediction model takes the volatile component, the vitrinite content and the inertinite content of each coal type as input variables, the caking index G value and the colloid layer thickness Y value of the mixed coking coal as output variables, and the actual measurement coking test data of blending coal are adopted for training and verification.
6. The method for preparing coking coal for improving selectivity of extremely difficult coal according to claim 1, wherein the step S4 further comprises a step of controlling stability of the dense medium suspension: monitoring the density and viscosity of the feeding suspension of the dense medium cyclone in real time; When the deviation between the density of the suspension and the set sorting density exceeds plus or minus 0.02g/cm 3 , adjusting the adding amount of the magnetite powder or the flow of the circulating medium to correct the density deviation; When the viscosity of the suspension exceeds 25 mPa.s, increasing the treatment capacity of the medium purification loop to reduce the content of non-magnetic fine mud in the suspension; And carrying out online ash detection on the separated clean coal products, and finely adjusting the separation density in real time according to the detection result.
7. The method for preparing coking coal for improving selectivity of extremely difficult coal preparation by washing according to claim 1, wherein the step S4 further comprises a step of collaborative optimization of a slime water system: carrying out mineral composition analysis on the coal slime water produced by mixing and washing, and determining the main clay mineral type in the coal slime water according to an analysis result; Selecting a flocculant type matched with the main clay mineral type according to the main clay mineral type, and controlling the adding amount of the flocculant to reduce the turbidity of the slime water below a preset turbidity standard; And monitoring the solid content in the circulating water, and starting the concentrated overflow discharging and clear water supplementing operation when the solid content exceeds the preset upper concentration limit.
8. The method for preparing coking coal with improved selectivity for extremely difficult coal dressing according to claim 1, wherein at least six standard density levels in the step S1 comprise 1.3g/cm 3 、1.4g/cm 3 、1.5g/cm 3 、1.6g/cm 3 、1.7g/cm 3 and 1.8g/cm 3 , the interpolation fitting adopts a cubic spline interpolation method, and the density resolution is not lower than 0.01 g/cm 3 .
9. A coking coal preparation system for improving the selectivity of extremely difficult coal by washing, characterized in that it is used for realizing a coking coal preparation method for improving the selectivity of extremely difficult coal by washing according to any one of claims 1 to 8, comprising: The coal quality analysis module is configured to acquire and process floating and sinking test data of the target extremely difficult coal and a plurality of candidate coal types respectively, generate density-yield distribution functions of the coal types, calculate density distribution complementarity indexes between the target extremely difficult coal and the candidate coal types, and screen compatible coal types meeting a preset threshold; The ratio optimizing module is in data connection with the coal quality analyzing module and is configured to receive the density-yield distribution function and the coking performance parameter of each coal, generate a mixed coal theoretical selectivity curve through weighted superposition, solve the optimal ratio of the maximization of the clean coal yield under the coking performance constraint and the ash constraint, and output an optimal ratio scheme and a corresponding sorting density set value; the coal blending and feeding module is in signal connection with the proportioning optimization module and is configured to control the feeding amount of the target extremely difficult coal and the matched coal types according to the optimal proportioning scheme, and the mixed coal is conveyed to a feeding port of the dense medium cyclone; The dense medium separation module comprises a dense medium cyclone and a medium circulation system and is configured to carry out density separation on the mixed coal according to the separation density set value to obtain coking clean coal; The quality monitoring module is arranged at the clean coal output end of the dense medium sorting module and is configured to detect clean coal ash in real time and feed back detection results to the proportion optimizing module and the dense medium sorting module so as to adjust proportion or sorting density.
10. The coking coal preparation system for improving the selectivity of extremely difficult-to-clean coal according to claim 9, wherein the coal quality analysis module comprises a sink-to-float data digitizing unit configured to convert discrete yield and ash data of each standard density level into a continuous density-yield distribution function by cubic spline interpolation, and a complementarity calculating unit configured to calculate a density distribution complementarity index from the density-yield distribution function and output a ranking result; the quality monitoring module comprises an online ash detector, wherein the online ash detector adopts a dual-energy X-ray transmission mode or a prompt gamma neutron activation analysis mode; The proportioning optimization module is internally provided with a nonlinear prediction model, and the nonlinear prediction model predicts the bonding index G value and the colloid layer thickness Y value of the mixed clean coal by taking the volatile component, the vitrinite content and the inertinite content of each coal as input variables.

Description

Coking coal preparation method for improving selectivity of extremely difficult coal dressing by washing Technical Field The invention relates to the technical field of coal washing and selecting processing, in particular to a coking coal preparation method for improving the selectivity of extremely difficult coal washing by matched washing. Background Coking coal is the basic raw material for metallurgical coke production, and the strength and reactivity of the coke are directly limited by the quality of the coal charged into the furnace. The national standard GB/T16417-2011 'coal selectivity evaluation method' takes near-heavy matter content delta +/-0.1 with the sorting density within the range of plus or minus 0.1 g/cm 3 as a selectivity criterion, and when the delta +/-0.1 exceeds 40%, the coal is judged to be extremely difficult to sort. In the coking coal resources ascertained in China, a considerable proportion of main production areas such as Shanxi, anhui and the like belong to extremely difficult coal dressing. The core characteristic of extremely difficult coal dressing is that the content of the medium density grade material is too high. Described in terms of a density-yield distribution function, exhibited a dramatic increase in cumulative yield over the density interval of 1.3 g/cm 3 to 1.5 g/cm 3, where the sink-float curve was nearly vertical. This means that at any single separation density, the difference in material density across the separation interface is very small and that dense medium cyclones are difficult to achieve effective separation even under optimal operating conditions. When 10.5% of the ash index of the clean coal is used as the ash index of a coal-selecting plant, the yield of the clean coal which is singly washed is often lower than 30%, the clean coal is difficult to maintain economically, and if the ash is relaxed to improve the yield, the caking index G value and the colloid layer thickness Y value of the clean coal do not reach the standard, and the clean coal cannot be used as coking raw materials. In the prior art, two treatment strategies are mainly adopted for extremely difficult coal dressing. The first is to improve the coal separation process, add a spiral separator, a TBS interference bed separator or a flotation column and other fine separation equipment, and perform secondary or tertiary selection on the roughed products. The method has the defects of large equipment investment, high operation energy consumption, sensitivity to feeding conditions and the like, and the essence is still that the sorting precision is attempted to be improved under the same material condition, the density composition of the feeding is not changed fundamentally, and the improvement range of extremely difficult coal dressing is limited. The second is to directly degrade the extremely difficult coal to the dynamic coal for sale, so that the sorting difficulty is avoided and the significant resource value loss is caused. Under the current market conditions, the price difference of coking coal and power coal is usually between 300 and 800 yuan per ton, calculated by a coal preparation plant with annual treatment capacity of 300 ten thousand tons, and the annual loss of economic benefit of degraded sales can reach hundreds of billions yuan. In the coking industry, coal blending technology has been used in the coking segment. The principle is that the coking performance of the coal in the furnace can be optimized by reasonable proportion because the coking coals of different varieties have differences in the components of coal and rock, volatile matters, cohesiveness and the like. However, the existing coal blending operation is carried out after coal dressing and before entering a coke oven, and the implicit premise is that various coal types participating in coal blending are respectively washed and selected as qualified clean coal. For extremely difficult coal dressing, qualified clean coal cannot be produced by washing and selecting alone, so that the clean coal cannot enter a subsequent coal blending coking process at all, and a break point on a technical path is formed. It is noted that there is often complementarity between the density-yield distribution functions of different coal types, namely that the density distribution functions of extremely difficult coal to sort are concentrated in the middle density interval (where defects are located), while the density distribution functions of some easy coal to sort are concentrated in the low density interval (where advantages are located). If the two are mixed in proper proportion before washing, the synthetic density distribution curve of the mixed coal shows the characteristics of reduced middle density level and increased low density level, thereby improving the feeding selectivity from the source. However, there is currently no systematic method for quantitatively evaluating the degree of complementarity of two coals in the d