CN113313394A - Coke quality evaluation method - Google Patents
Coke quality evaluation method Download PDFInfo
- Publication number
- CN113313394A CN113313394A CN202110613492.1A CN202110613492A CN113313394A CN 113313394 A CN113313394 A CN 113313394A CN 202110613492 A CN202110613492 A CN 202110613492A CN 113313394 A CN113313394 A CN 113313394A
- Authority
- CN
- China
- Prior art keywords
- index
- coke
- indexes
- comprehensive
- characteristic
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 239000000571 coke Substances 0.000 title claims abstract description 121
- 238000000034 method Methods 0.000 title claims abstract description 23
- 238000013441 quality evaluation Methods 0.000 title claims abstract description 17
- 238000011156 evaluation Methods 0.000 claims abstract description 46
- 239000011159 matrix material Substances 0.000 claims abstract description 42
- 238000012545 processing Methods 0.000 claims abstract description 4
- 239000002245 particle Substances 0.000 claims description 21
- 230000014509 gene expression Effects 0.000 claims description 17
- 239000000126 substance Substances 0.000 claims description 9
- 239000013598 vector Substances 0.000 claims description 6
- 238000005299 abrasion Methods 0.000 claims description 5
- 238000006243 chemical reaction Methods 0.000 claims description 5
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims description 4
- 229910052799 carbon Inorganic materials 0.000 claims description 3
- 239000002131 composite material Substances 0.000 claims description 3
- 230000009467 reduction Effects 0.000 abstract description 4
- 230000007547 defect Effects 0.000 abstract description 3
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 6
- 238000004458 analytical method Methods 0.000 description 5
- 230000009471 action Effects 0.000 description 4
- 239000003795 chemical substances by application Substances 0.000 description 3
- 230000001186 cumulative effect Effects 0.000 description 3
- 229910052742 iron Inorganic materials 0.000 description 3
- 238000005303 weighing Methods 0.000 description 3
- 238000003723 Smelting Methods 0.000 description 2
- 239000003638 chemical reducing agent Substances 0.000 description 2
- 239000003245 coal Substances 0.000 description 2
- 238000005260 corrosion Methods 0.000 description 2
- 230000007797 corrosion Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000010438 heat treatment Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 239000000243 solution Substances 0.000 description 2
- 229910052717 sulfur Inorganic materials 0.000 description 2
- 229910000831 Steel Inorganic materials 0.000 description 1
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 description 1
- 229910052783 alkali metal Inorganic materials 0.000 description 1
- 150000001340 alkali metals Chemical class 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000005255 carburizing Methods 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000006731 degradation reaction Methods 0.000 description 1
- 238000004090 dissolution Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000001125 extrusion Methods 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 238000002347 injection Methods 0.000 description 1
- 239000007924 injection Substances 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 239000000843 powder Substances 0.000 description 1
- 239000002893 slag Substances 0.000 description 1
- 239000010959 steel Substances 0.000 description 1
- 239000011593 sulfur Substances 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06395—Quality analysis or management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Physics (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Computational Mathematics (AREA)
- Operations Research (AREA)
- General Engineering & Computer Science (AREA)
- Software Systems (AREA)
- Strategic Management (AREA)
- Databases & Information Systems (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Algebra (AREA)
- Game Theory and Decision Science (AREA)
- Marketing (AREA)
- Computing Systems (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Probability & Statistics with Applications (AREA)
- Coke Industry (AREA)
Abstract
The invention discloses a coke quality evaluation method, which comprises the following steps: establishing an evaluation index system of coke quality; forming an original data matrix X by the evaluation indexes of each coke sample in the period, and carrying out standardized dimensionless processing on the original data matrix X to obtain a standardized matrix Z; calculating the correlation coefficient of each evaluation index in the standardized matrix Z, and constructing a correlation coefficient matrix R; calculating the eigenvalue and eigenvector of the correlation coefficient matrix R, and constructing a comprehensive characteristic index based on one eigenvector; and determining the previous p comprehensive characteristic indexes with large variance contribution rate, and calculating the weights of the previous p comprehensive characteristic indexes to obtain the comprehensive evaluation index of the coke quality. The defects that man-made subjective influence factors are large, the number of indexes is large, the indexes are overlapped and the like are overcome, a plurality of coke quality indexes are converted into a plurality of comprehensive characteristic indexes on the premise of losing little information by using a dimension reduction thought, and the evaluation method for comprehensively reflecting the coke quality is established.
Description
Technical Field
The invention belongs to the technical field of coke for blast furnace iron making, and particularly relates to a coke quality evaluation method.
Background
Coke is a vital fuel for blast furnace ironmaking, and the quality of the coke directly influences various technical and economic indexes of the blast furnace. The coke mainly plays roles of a heating agent, a reducing agent, a carburizing agent and a material column framework in the blast furnace. With the continuous progress of iron-making technology, the coal injection quantity of a blast furnace is continuously improved, the action of a heating agent and a reducing agent of coke is partially replaced by the injected coal powder, meanwhile, the load of the coke in the blast furnace is increased due to the reduction of coke ratio, and the action of a stock column framework of the coke is more important in the smelting process. The coke is subjected to the influence of mechanical actions such as collision, extrusion, abrasion and the like in the blast furnace, and is simultaneously subjected to the influence of chemical actions such as dissolution loss reaction, alkali metal corrosion, slag iron corrosion and the like, and is continuously degraded from top to bottom. Under the condition of intensified smelting, the coke only has good enough quality, and can fully play the role of the coke in blast furnace iron making in the process of gradual degradation, so that the blast furnace is kept to be stable and smooth.
At present, no uniformly approved method for evaluating coke quality exists in the iron-making industry. According to researches such as 'technical research on a system for evaluating the quality of coke charged into a steel-bearing blast furnace', and the like, different weights are given to various indexes of the coke for scoring evaluation, so that artificial subjective influence factors are large, the quantity of the indexes is large, the indexes are overlapped, and the real quality of the coke cannot be objectively and comprehensively reflected.
Disclosure of Invention
The invention provides a coke quality evaluation method, aiming at improving the problems.
The invention is realized in such a way, and the coke quality evaluation method specifically comprises the following steps:
s1, establishing an evaluation index system of coke quality;
s2, forming the evaluation indexes of each coke sample in the period into an original data matrix X, and carrying out standardized dimensionless processing on the original data matrix X to obtain a standardized matrix Z;
s3, calculating the correlation coefficient of each evaluation index in the standardized matrix Z, and constructing a correlation coefficient matrix R;
s4, calculating the eigenvalue and the eigenvector of the correlation coefficient matrix R, and constructing a comprehensive characteristic index based on the eigenvector;
s5, determining the first p comprehensive characteristic indexes with large variance contribution rate, and calculating the weight of the first p comprehensive characteristic indexes to obtain the comprehensive evaluation index of coke quality.
Further, the evaluation index system of the coke quality comprises: cold strength index, hot performance index, physical and chemical index, wherein,
the cold strength indicators include: crushing strength M40And abrasion resistance M10;
The thermal state performance indexes include: reactive CRI and post-reaction intensity CSR;
the physical and chemical indexes comprise: ash content AdMoisture content H2O, S and VdafFixed carbon CadThe ratio L of the particle size of more than 80mm80The particle size is 60-80 mm and the ratio L60The particle size is 40-60 mm40The particle size of 25-40 mm is L25Coke breeze content L0Average particle size DAverageAnd powder-to-coke ratio CFine coke。
Further, the eigenvalues of the correlation coefficient matrix R are sorted from large to small as follows: lambda [ alpha ]1≧λ2…≧λj…≧λm≧ 0, and corresponding feature vector u1、u2…uj…umWherein u isj=[u1j,u2j,u3j,…,umj]TThe overall characteristic index is expressed as follows:
F1=u11z1+u21z2+…+uj1zj+…+um1zm
F2=u12z1+u22z2+…+uj2zj+…+um2zm
…
Fj=u1jz1+u2jz2+…+ujjzj+…+umjzm
…
Fm=u1mz1+u2mz2+…+ujmzj+…+ummzm
wherein z is1,z2…zj…zmFor standardized evaluation index, FmIs the m-th comprehensive characteristic index.
Further, the characteristic index coefficient u is integratedijThe expression (c) is specifically as follows:
Kijis the value of the ith evaluation index in the jth comprehensive characteristic index in the comprehensive characteristic index load matrix, lambdajAnd representing the characteristic value of the jth comprehensive characteristic index.
Further, the expression of the coke quality comprehensive evaluation index is specifically as follows:
F=ω1F1+ω2F2+…ωjFj+…ωpFp
ω1、ω2…ωj…ωpthe weight of each comprehensive characteristic index of the coke is calculated by the following formula:
λjis the characteristic value, lambda, of the jth composite characteristic indexkThe characteristic value of the k-th comprehensive characteristic index is 1 to p
The invention overcomes the defects of large artificial subjective influence factor, large index quantity, overlapping of indexes and the like, converts a plurality of coke quality indexes into a plurality of comprehensive characteristic indexes by using a dimension reduction thought on the premise of losing little information, establishes an evaluation method for comprehensively reflecting the coke quality, provides a technical reference basis for purchasing coke, and can lead a blast furnace operator to prejudge the influence of the coke on the furnace condition in advance by dynamically tracking the quality fluctuation condition of the coke for the blast furnace, make operation countermeasures and reduce the blast furnace iron-making cost.
Drawings
FIG. 1 is a macadam map of coke command evaluation parameters provided by an embodiment of the invention;
FIG. 2 is a flow chart of a coke quality evaluation method according to an embodiment of the present invention.
Detailed Description
The following detailed description of the embodiments of the present invention will be given in order to provide those skilled in the art with a more complete, accurate and thorough understanding of the inventive concept and technical solutions of the present invention.
Fig. 2 is a flowchart of a coke quality evaluation method according to an embodiment of the present invention, where the method includes the following steps:
and S1, establishing an evaluation index system of coke quality.
And in a statistical period, selecting an evaluation index capable of reflecting the coke quality from the production detection system. The coke evaluation indexes are classified into 3 types including cold strength indexes, hot performance indexes and physical and chemical indexes, wherein the cold strength indexes comprise: crushing strength M40And abrasion resistance M10(ii) a The thermal state performance indexes include: reactive CRI and post-reaction intensity CSR; the physical and chemical indexes comprise: ash content AdMoisture content H2O, S and VdafFixed carbon CadThe ratio L of the particle size of more than 80mm80The particle size is 60-80 mm and the ratio L60The particle size is 40-60 mm40The particle size of 25-40 mm is L25Coke breeze content L0Average particle size DAverageAnd powder-to-coke ratio CFine coke。
S2, carrying out standardized dimensionless processing on the original data matrix X consisting of the m evaluation indexes of the n coke samples in a statistical period to obtain a standardized matrix Z. The expression of the original data matrix X is X ═ X (X)ij)n×mThe expression of the normalized matrix Z is Z ═ Z (Z)ij)n×m;
xijRepresenting the jth index value of the ith coke sample, wherein 1 is less than or equal to i less than or equal to n, and 1 is less than or equal to j less than or equal to m, namely the jth column element at the ith row in the original data matrix X; z is a radical ofijThe j index value of the ith coke sample after the normalization treatment is represented, namely the i row and the j column of elements in the normalization matrix Z;the arithmetic mean value of the jth coke original index, namely the arithmetic mean value of the jth column element in the original data matrix X; sigmajIs the standard deviation of the j th coke original index, namely the standard deviation of the j th column element in the original data matrix X.
S3, calculating a correlation coefficient between the evaluation indexes in the normalized matrix Z, and constructing a correlation coefficient matrix R where R is (R)jk)m×m;
Is the arithmetic mean of the j column elements in the normalized matrix Z; r isjkIs a correlation coefficient between the j index and the k index, rjk=rkj,rjj=1,1≦j≦m,1≦k≦m。
S4, calculating a characteristic value and a characteristic vector of the correlation coefficient matrix R, and constructing a comprehensive characteristic index based on one characteristic vector;
solving the characteristic equation R-Lambda I to obtain the characteristic value Lambda which is ordered from large to small1≧λ2…≧λj…≧λm≧ 0, and corresponding feature vector u1、u2…uj…umWherein u isj=[u1j,u2j,u3j…umj]T. And (3) establishing m comprehensive characteristic indexes according to the characteristic vectors:
z1,z2…zj…zmfor standardized evaluation index, F1Weighing the first overall characteristic index, F2Weighing the second overall characteristic index, FjWeighing the jth comprehensive characteristic index, FmThe m-th comprehensive characteristic index is called.
And S5, determining the number of the comprehensive characteristic indexes. Sorting the variance contribution rates of the comprehensive characteristic indexes in a descending order, calculating the variance contribution rate and the accumulated variance contribution rate of each comprehensive characteristic index, comprehensively determining the first p comprehensive characteristic indexes according to the principle that the accumulated variance contribution rate reaches a specific value (such as 75%, 80% and 85%) or the characteristic value is more than 1 and combining a lithotripsy (such as shown in figure 1), and using F to comprehensively determine the first p comprehensive characteristic indexes1、F2…Fj…FpP comprehensive characteristic indexes are provided, namely the comprehensive characteristic indexes represent the original m indexes to comprehensively analyze the coke quality. To the aboveComprehensive characteristic index F of coke quality obtained by comprehensive characteristic index analysis1、F2…Fj…FpAnalysis is performed and the physical significance represented by the overall characteristic index of coke quality is explained.
αjThe variance contribution rate, S, of the composite characteristic index jpP ≦ m, which is the cumulative contribution of the first p synthetic performance indicators.
In actual calculation, the characteristic value, the total variance interpretation table and the comprehensive characteristic index load matrix of the comprehensive characteristic index can be obtained through SPSS software, and the coefficient of each original evaluation index in different linear combinations of the comprehensive characteristic indexes, namely the comprehensive characteristic index coefficient uijAnd (4) solving the expression of the previous p comprehensive characteristic indexes.
KijIs the value of the ith evaluation index in the jth comprehensive characteristic index in the comprehensive characteristic index load matrix, lambdajIs the characteristic value of the jth comprehensive characteristic index.
(6) And calculating the weights of the previous p comprehensive characteristic indexes to obtain the coke quality comprehensive evaluation index.
F=ω1F1+ω2F2+…ωjFj+…ωpFp (10)
F is a comprehensive evaluation index of coke quality, F1、F2…Fj…FpTo reflect the overall characteristic index of a certain property of the coke, omega1、ω2…ωj…ωpThe weight of each comprehensive characteristic index of the coke.
Note: f is determined according to the physical significance represented by each comprehensive characteristic index and the requirement of coke on each comprehensive characteristic index1、F2…Fj…FpSign in the comprehensive evaluation index expression F.
By calculating the specific numerical value of the coke daily comprehensive evaluation index and tracking the change trend, a blast furnace operator can predict the influence of coke quality fluctuation on the furnace condition in advance and make positive countermeasures.
Compared with the existing coke quality evaluation method, the method overcomes the defects of large artificial subjective influence factor, large index quantity, overlapping of indexes and the like, converts a plurality of coke quality indexes into a plurality of comprehensive characteristic indexes by using the dimension reduction thought on the premise of losing little information, establishes an evaluation method for comprehensively reflecting the coke quality, provides a technical reference basis for purchasing the coke, and can lead a blast furnace operator to prejudge the influence of the coke on the furnace condition in advance by dynamically tracking the quality fluctuation condition of the coke for the blast furnace, make operation countermeasures and reduce the blast furnace iron-making cost.
The invention is further explained in detail with reference to the attached drawings, and the coke quality evaluation method comprises the following steps:
(1) and establishing a coke quality evaluation index system. In a statistical period, an evaluation index and a numerical value which can reflect the coke quality are selected from a production detection system. The coke evaluation index includes cold strength index, hot performance index and physical and chemical index, wherein the cold strength index includes crushing strength M40And abrasion resistance M10(ii) a The hot state performance index comprises reactive CRI and post-reaction strength CSR, and the physical and chemical index comprises ash AdMoisture content H2O, S, and L, the particle size is greater than 80mm80The particle size is 60-80 mm and the ratio L60The particle size is 40-60 mm40The particle size of 25-40 mm is L25Coke breeze content L0Average particle size DAverageAnd powder-to-coke ratio CFine cokeTotal 3 classes of 14 indices.
(2) And carrying out standardized dimensionless treatment on the collected and sorted coke quality index value of 3 months.
(3) Calculating the correlation coefficient among the indexes according to the normalized index values, and constructing a correlation coefficient matrix R, wherein R is (R)jk)14×14. As can be seen from Table 1, the overlap between some indexes is severe, such as CRI and CSR, which are highly linear.
TABLE 1 correlation coefficient of coke index
Parameter(s) | CRI | CSR | M40 | M10 | Ad | H2O | S | L80 | L60 | L40 | L25 | L0 | DAverage | CFine coke |
CRI | 1.000 | -0.993 | 0.086 | -0.049 | -0.141 | 0.205 | -0.061 | 0.147 | 0.062 | 0.004 | 0.065 | -0.093 | 0.032 | -0.139 |
CSR | -0.993 | 1.000 | -0.096 | 0.062 | 0.129 | -0.202 | 0.084 | -0.139 | -0.050 | 0.011 | -0.048 | 0.109 | -0.017 | 0.112 |
M40 | 0.086 | -0.096 | 1.000 | -0.249 | 0.004 | 0.260 | -0.164 | -0.121 | 0.009 | -0.092 | -0.037 | 0.027 | -0.063 | 0.122 |
M10 | -0.049 | 0.062 | -0.249 | 1.000 | -0.159 | -0.141 | 0.266 | -0.056 | 0.042 | 0.112 | 0.086 | 0.084 | 0.086 | 0.179 |
Ad | -0.141 | 0.129 | 0.004 | -0.159 | 1.000 | 0.283 | -0.257 | -0.016 | -0.032 | -0.030 | -0.131 | -0.018 | -0.047 | 0.059 |
H2O | 0.205 | -0.202 | 0.260 | -0.141 | 0.283 | 1.000 | -0.124 | -0.039 | -0.009 | -0.004 | 0.024 | -0.022 | -0.004 | -0.168 |
S | -0.061 | 0.084 | -0.164 | 0.266 | -0.257 | -0.124 | 1.000 | 0.147 | 0.125 | 0.216 | 0.197 | 0.192 | 0.199 | -0.022 |
L80 | 0.147 | -0.139 | -0.121 | -0.056 | -0.016 | -0.039 | 0.147 | 1.000 | 0.826 | 0.804 | 0.741 | 0.587 | 0.845 | -0.077 |
L60 | 0.062 | -0.050 | 0.009 | 0.042 | -0.032 | -0.009 | 0.125 | 0.826 | 1.000 | 0.928 | 0.810 | 0.685 | 0.956 | -0.031 |
L40 | 0.004 | 0.011 | -0.092 | 0.112 | -0.030 | -0.004 | 0.216 | 0.804 | 0.928 | 1.000 | 0.886 | 0.693 | 0.992 | -0.093 |
L25 | 0.065 | -0.048 | -0.037 | 0.086 | -0.131 | 0.024 | 0.197 | 0.741 | 0.810 | 0.886 | 1.000 | 0.522 | 0.909 | -0.029 |
L0 | -0.093 | 0.109 | 0.027 | 0.084 | -0.018 | -0.022 | 0.192 | 0.587 | 0.685 | 0.693 | 0.522 | 1.000 | 0.708 | -0.055 |
DAverage | 0.032 | -0.017 | -0.063 | 0.086 | -0.047 | -0.004 | 0.199 | 0.845 | 0.956 | 0.992 | 0.909 | 0.708 | 1.000 | -0.071 |
CFine coke | -0.139 | 0.112 | 0.122 | 0.179 | 0.059 | -0.168 | -0.022 | -0.077 | -0.031 | -0.093 | -0.029 | -0.055 | -0.071 | 1.000 |
(4) And calculating the eigenvalue and eigenvector of the correlation coefficient matrix R. If the 14 original indexes of coke are directly used for comprehensive evaluation, information is overlapped inevitably, and the objectivity of an evaluation result is influenced. SPSS software is used for carrying out comprehensive characteristic index analysis on the 14 indexes, and the characteristic value and the variance contribution rate of the correlation coefficient matrix R are shown in a table 2.
TABLE 2 extraction of main components of coke Performance index
(5) And determining the number of the comprehensive characteristic indexes. Comprehensively determining the first 5 comprehensive characteristics according to the principle that the cumulative variance contribution rate is more than 75% or the characteristic value is more than 1 and by combining the lithotripsy chart 1Index, using F1,F2,…F5The total of 5 main components, namely the comprehensive characteristic index represents the original 14 indexes to carry out comprehensive analysis on the coke quality. The cumulative variance contribution rate of 5 comprehensive characteristic indexes is 79.029%, which exceeds 75%, and the method has strong explanatory power.
The characteristic value, the total variance interpretation table and the comprehensive characteristic index load matrix (table 3) of the comprehensive characteristic indexes can be obtained through SPSS software, and the coefficients of all the evaluation indexes in different linear combinations of the comprehensive characteristic indexes are determined, namely, the expressions of the first 5 comprehensive characteristic indexes are solved.
TABLE 3 comprehensive characteristic index load matrix K extracted from evaluation of coke propertiesij
The initial load matrix of the comprehensive characteristic index is combined with the characteristic value, so that the eigenvector of the comprehensive characteristic index can be obtained by solving, and the eigenvector is multiplied by the standardized coke quality index data, so that a comprehensive characteristic index expression is obtained:
F1=0.011*CRI-0.005*CSR-0.007*M40+0.021*M10-0.003*Ad+0.013*H2O+0.083*S+0.390*L80+0.427*L60+0.434*L40+0.398*L25+0.339*L0+0.442*Daverage-0.022*CFine coke
F2=0.679*CRI-0.679*CSR+0.053*M40+0.026*M10-0.133*Ad+0.172*H2O-0.039*S+0.085*L80+0.027*L60-0.010*L40+0.047*L25-0.106*L0+0.009*DAverage-0.067*CFine coke
F3=0.017*CRI-0.029*CSR+0.058*M40-0.211*M10+0.713*Ad+0.477*H2O-0.452*S-0.007*L60-0.031*L40-0.079*L25-0.053*L0-0.034*DAverage+0.012*CFine coke
F4=0.025*CRI-0.037*CSR+0.780*M40-0.513*M10-0.134*Ad+0.157*H2O-0.244*S-0.055*L80+0.026*L60-0.081*L40-0.015*L25+0.039*L0-0.044*DAverage+0.103*CFine coke
F5=-0.054*CRI+0.035*CSR+0.161*M40+0.463*M10+0.063*Ad-0.158*H2O-0.017*S-0.077*L80+0.024*L60-0.022*L40+0.021*L25-0.006*L0-0.009*DAverage+0.848*CFine coke
Note: the respective variables are data normalized by the original variables.
L80,L60,L40,L25,L0And DAverageWhen 6 indexes have higher load on the 1 st comprehensive characteristic index, namely the absolute value of the coefficient is more than 0.6, the 1 st comprehensive characteristic index basically reflects the information of the indexes, F is1The method is defined as an index of comprehensive particle size characteristics of the coke, and the index accounts for 36.242% of the total information of the coke mass, and has strong explanatory power. F1The coefficients of 6 granularity indexes in the expression are all positive, and F is required1The larger the better.
The 2 nd comprehensive characteristic index basically reflects the information of CRI and CSR indexes, and F is2Defined as the comprehensive high-temperature characteristic index of coke. The interpretation amount of the index in the total coke mass information is 15.965%, and the index has strong interpretation strength. F2In the expression, the CRI coefficient is positive, the CSR coefficient is negative, and F is required2The smaller the better.
The 3 rd comprehensive characteristic index basically reflects Ad,H2Information of O, S index, F3Is defined as the index of the comprehensive composition characteristic of the coke. The interpretation amount of the index in the total coke mass information is 11.777%, and the index has strong interpretation strength. F3Water content in the expression H2Coefficient of O is positive, ash AdThe coefficient is positive and the absolute value of the coefficient is maximum, the coefficient of sulfur content S is negative, and F is required3The smaller the better.
The 4 th comprehensive characteristic index basically reflects M40,M10Information of index, F4Is defined as the index of the comprehensive cold strength characteristic of coke, F4In the expression M40Coefficient of (1) is positive, M10Has a negative coefficient of (A), F4The larger the better.
The 5 th comprehensive characteristic index basically reflects CFine cokeInformation of index, F5Is defined as the comprehensive coke breeze characteristic index of coke, F5The coefficient of the coke powder ratio in the expression is positive, F5The smaller the better.
(6) And calculating the weights of the 5 comprehensive characteristic indexes to obtain a coke quality comprehensive evaluation index expression. Establishing a coke quality evaluation method by taking the ratio of the characteristic value corresponding to each comprehensive characteristic index to the sum of the total characteristic values of the extracted comprehensive characteristic indexes as weight, and F according to the requirements of the coke on each comprehensive characteristic index1And F4Taking a positive number, F2,F3And F5Taking a negative number.
F=0.454F1-0.191F2-0.135F3+0.116F4-0.105F5
According to the comprehensive evaluation index expression of coke analysis, the daily comprehensive evaluation value F of the coke quality can be calculated, the quality fluctuation of the coke is objectively evaluated and analyzed, and human influence factors are eliminated.
The invention has been described above with reference to the accompanying drawings, it is obvious that the invention is not limited to the specific implementation in the above-described manner, and it is within the scope of the invention to apply the inventive concept and solution to other applications without substantial modification.
Claims (5)
1. The coke quality evaluation method is characterized by comprising the following steps:
s1, establishing an evaluation index system of coke quality;
s2, forming the evaluation indexes of each coke sample in the period into an original data matrix X, and carrying out standardized dimensionless processing on the original data matrix X to obtain a standardized matrix Z;
s3, calculating the correlation coefficient of each evaluation index in the standardized matrix Z, and constructing a correlation coefficient matrix R;
s4, calculating the eigenvalue and the eigenvector of the correlation coefficient matrix R, and constructing a comprehensive characteristic index based on the eigenvector;
s5, determining the first p comprehensive characteristic indexes with large variance contribution rate, and calculating the weight of the first p comprehensive characteristic indexes to obtain the comprehensive evaluation index of coke quality.
2. The coke quality evaluation method according to claim 1, wherein the evaluation index system for coke quality comprises: cold strength index, hot performance index, physical and chemical index, wherein,
the cold strength indicators include: crushing strength M40And abrasion resistance M10;
The thermal state performance indexes include: reactive CRI and post-reaction intensity CSR;
the physical and chemical indexes comprise: ash content AdMoisture content H2O, S and VdafFixed carbon CadThe ratio L of the particle size of more than 80mm80The particle size is 60-80 mm and the ratio L60The particle size is 40-60 mm40The particle size of 25-40 mm is L25Coke breeze content L0Average particle size DAverageAnd powder-to-coke ratio CFine coke。
3. The coke quality evaluation method of claim 1, wherein the eigenvalues of the correlation coefficient matrix R are sorted from large to small as: lambda [ alpha ]1≧λ2…≧λj…≧λm≧ 0, and corresponding feature vector u1、u2…uj…umWherein u isj=[u1j,u2j,u3j,…,umj]TThe overall characteristic index is expressed as follows:
F1=u11z1+u21z2+…+uj1zj+…+um1zm
F2=u12z1+u22z2+…+uj2zj+…+um2zm
…
Fj=u1jz1+u2jz2+…+ujjzj+…+umjzm
…
Fm=u1mz1+u2mz2+…+ujmzj+…+ummzm
wherein z is1,z2…zj…zmFor standardized evaluation index, FmIs the m-th comprehensive characteristic index.
4. The coke quality evaluation method according to claim 2, wherein the overall characteristic index coefficient u isijThe expression (c) is specifically as follows:
Kijis the value of the ith evaluation index in the jth comprehensive characteristic index in the comprehensive characteristic index load matrix, lambdajAnd representing the characteristic value of the jth comprehensive characteristic index.
5. The coke quality evaluation method according to claim 2, wherein the expression of the coke quality comprehensive evaluation index is as follows:
F=ω1F1+ω2F2+…ωjFj+…ωpFp
ω1、ω2…ωj…ωpthe weight of each comprehensive characteristic index of the coke is calculated by the following formula:
λjis the characteristic value, lambda, of the jth composite characteristic indexkAnd the characteristic value of the kth comprehensive characteristic index is 1 to p.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110613492.1A CN113313394A (en) | 2021-06-02 | 2021-06-02 | Coke quality evaluation method |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110613492.1A CN113313394A (en) | 2021-06-02 | 2021-06-02 | Coke quality evaluation method |
Publications (1)
Publication Number | Publication Date |
---|---|
CN113313394A true CN113313394A (en) | 2021-08-27 |
Family
ID=77376967
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202110613492.1A Pending CN113313394A (en) | 2021-06-02 | 2021-06-02 | Coke quality evaluation method |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN113313394A (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113780810A (en) * | 2021-09-10 | 2021-12-10 | 重庆钢铁股份有限公司 | Coke purchasing decision method |
CN117470721A (en) * | 2023-12-28 | 2024-01-30 | 山西建龙实业有限公司 | Method for measuring and evaluating high-temperature degradation strength and granularity degradation behavior of metallurgical coke |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8417715B1 (en) * | 2007-12-19 | 2013-04-09 | Tilmann Bruckhaus | Platform independent plug-in methods and systems for data mining and analytics |
CN103577681A (en) * | 2013-06-26 | 2014-02-12 | 长沙理工大学 | Factor analysis-based quantitative evaluation method on of boiler efficiency influence indexes |
CN105303468A (en) * | 2015-11-20 | 2016-02-03 | 国网天津市电力公司 | Comprehensive evaluation method of smart power grid construction based on principal component cluster analysis |
CN110717687A (en) * | 2019-10-16 | 2020-01-21 | 青岛海信网络科技股份有限公司 | Evaluation index acquisition method and system |
CN111401774A (en) * | 2020-03-26 | 2020-07-10 | 武汉钢铁有限公司 | Comprehensive evaluation method for coke quality |
CN112613583A (en) * | 2021-01-05 | 2021-04-06 | 广东工业大学 | High-frequency information extraction clustering method for low-frequency noise face image |
-
2021
- 2021-06-02 CN CN202110613492.1A patent/CN113313394A/en active Pending
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8417715B1 (en) * | 2007-12-19 | 2013-04-09 | Tilmann Bruckhaus | Platform independent plug-in methods and systems for data mining and analytics |
CN103577681A (en) * | 2013-06-26 | 2014-02-12 | 长沙理工大学 | Factor analysis-based quantitative evaluation method on of boiler efficiency influence indexes |
CN105303468A (en) * | 2015-11-20 | 2016-02-03 | 国网天津市电力公司 | Comprehensive evaluation method of smart power grid construction based on principal component cluster analysis |
CN110717687A (en) * | 2019-10-16 | 2020-01-21 | 青岛海信网络科技股份有限公司 | Evaluation index acquisition method and system |
CN111401774A (en) * | 2020-03-26 | 2020-07-10 | 武汉钢铁有限公司 | Comprehensive evaluation method for coke quality |
CN112613583A (en) * | 2021-01-05 | 2021-04-06 | 广东工业大学 | High-frequency information extraction clustering method for low-frequency noise face image |
Non-Patent Citations (4)
Title |
---|
卢光辉等: "大中型高炉用冶金焦常规质量指标的相关性分析", 《河北冶金》, no. 1, pages 1 * |
李新宇;张建良;苏步新;姚朝权;刘兴乐;张超;: "基于主成分分析的高炉用天然块矿性能评价", 《中南大学学报(自然科学版)》, vol. 47, no. 9, pages 2943 - 2950 * |
罗吉敖: "《炼铁学》", 30 June 1994, 冶金工业出版社, pages: 59 - 64 * |
高新华等: "基于主成分聚类分析的智能电网建设综合评价", 《电网技术》, vol. 37, no. 8, pages 1 * |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113780810A (en) * | 2021-09-10 | 2021-12-10 | 重庆钢铁股份有限公司 | Coke purchasing decision method |
CN117470721A (en) * | 2023-12-28 | 2024-01-30 | 山西建龙实业有限公司 | Method for measuring and evaluating high-temperature degradation strength and granularity degradation behavior of metallurgical coke |
CN117470721B (en) * | 2023-12-28 | 2024-03-26 | 山西建龙实业有限公司 | Method for measuring and evaluating high-temperature degradation strength and granularity degradation behavior of metallurgical coke |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN113313394A (en) | Coke quality evaluation method | |
CN116501003B (en) | Processing control method and system for smelting special steel | |
Campos et al. | Theorical and experimental determination of the forming limit diagram for the AISI 304 stainless steel | |
CN114611844B (en) | Method and system for determining alloy addition amount in converter tapping process | |
CN110472349A (en) | A kind of hot-rolled steel performance prediction method based on EEMD and depth convolutional network | |
CN104899425A (en) | Variable selection and forecast method of silicon content in molten iron of blast furnace | |
Yuan et al. | Modeling and optimization of coal blending and coking costs using coal petrography | |
Afshoon et al. | Combining Kriging meta models with U-function and K-Means clustering for prediction of fracture energy of concrete | |
CN107169205A (en) | A kind of classification model construction method of iron ore | |
Ge et al. | Hot deformation behavior and artificial neural network modeling of β-γ TiAl alloy containing high content of Nb | |
CN112884359A (en) | Electric power spot market risk assessment method | |
Shikalgar et al. | Analysis of p-SPT specimens using Gurson parameters ascertained by Artificial Neural Network | |
Shen et al. | Comparison of two constitutive modelling methods in application of TC16 alloy at the elevated deformation temperature | |
CN113177364B (en) | Soft measurement modeling method for temperature of blast furnace tuyere convolution zone | |
CN113553712A (en) | Powder metallurgy mixed material formula modeling and control method based on multiple regression | |
Chen et al. | A nonlinear fatigue damage accumulation model under variable amplitude loading considering the loading sequence effect | |
Liu et al. | Research on fatigue life evaluation method of shafts based on small sample P–S–N | |
Wu et al. | Deformation resistance prediction of tandem cold rolling based on grey wolf optimization and support vector regression | |
CN109242210B (en) | Automatic recommendation method for optimal proportioning of pellet raw materials | |
CN111798023A (en) | Method for predicting comprehensive coke ratio in steelmaking sintering production | |
Ren et al. | Deep learning-based method for microstructure-property linkage of dual-phase steel | |
CN115392104A (en) | Method for predicting mechanical property of cold-rolled continuous annealing strip steel based on annealing process | |
Chen et al. | An intelligent online detection approach based on big data for mechanical properties of hot-rolled strip | |
Gocheva-Ilieva et al. | Study of the tensile strength of alloy steels using polynomial regression | |
Won et al. | Artificial Neural Network for Predicting Edge Stretchability in Hole Expansion Test with Gpa-Grade Steel |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination |