CN112907042A - Coking coal business operation method, device computer equipment and storage medium - Google Patents

Coking coal business operation method, device computer equipment and storage medium Download PDF

Info

Publication number
CN112907042A
CN112907042A CN202110129866.2A CN202110129866A CN112907042A CN 112907042 A CN112907042 A CN 112907042A CN 202110129866 A CN202110129866 A CN 202110129866A CN 112907042 A CN112907042 A CN 112907042A
Authority
CN
China
Prior art keywords
coking coal
sub
quality
calculating
coking
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
Application number
CN202110129866.2A
Other languages
Chinese (zh)
Inventor
曾令鹏
范国光
程启国
刘克辉
余骏
李德平
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
SGIS Songshan Co Ltd
Original Assignee
SGIS Songshan Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by SGIS Songshan Co Ltd filed Critical SGIS Songshan Co Ltd
Priority to CN202110129866.2A priority Critical patent/CN112907042A/en
Publication of CN112907042A publication Critical patent/CN112907042A/en
Pending legal-status Critical Current

Links

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
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • 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
    • 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
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/20—Identification of molecular entities, parts thereof or of chemical compositions
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/30—Prediction of properties of chemical compounds, compositions or mixtures
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Abstract

The embodiment of the invention provides a coking coal service operation method, a coking coal service operation device, computer equipment and a storage medium, wherein the method comprises the following steps: detecting a plurality of indicators related to quality at least in the dimension of coking; calculating a total mass value characterizing mass in at least the coking dimension for the coking coal based on the plurality of indicators; calculating the cost performance of the coking coal relative to metallurgical behavior according to the total mass value; and performing business operation on the coking coal according to the cost performance. By combining the characteristic of stronger coking property of coking coal, the total quality value of the coking coal obtained under the dimension of the coking property can comprehensively reflect the quality of the coking coal, the reliability of reference data for guiding the coking coal business operation is improved, the operability and the adaptability of metallurgical behavior according to the cost performance of the coking coal are enhanced, the accuracy of business operation execution aiming at the coking coal is improved, the financial and labor costs for screening and purchasing the coking coal are reduced, various coking coals can be reasonably utilized, and the possibility of improving the utilization rate of coking coal resources is increased.

Description

Coking coal business operation method, device computer equipment and storage medium
Technical Field
The embodiment of the invention relates to the technical field of metallurgical coking, in particular to a coking coal business operation method, a coking coal business operation device, computer equipment and a storage medium.
Background
The coking coal is a coal type of coking coal and is also a skeleton variety for coal blending and coking. In the process of coking coal, generally, the proportion of coking coal is about half of the total proportion of the coking coal, but the coking coal resources are scarce, and the storage capacity of the coking coal resources is only about 20 percent of the coking coal resources.
In order to scientifically and effectively utilize coking coal, research on the coal quality of the coking coal is increased by various large coking enterprises and academic institutions. In the prior art, conventional industrial analysis, caking index and maximum colloidal layer thickness detection, Olympic expansion degree analysis, Kirschner flow degree analysis, coal rock analysis, small coke oven coking experiments and the like exist, and the coking coal quality is comprehensively evaluated by using detection and experimental data.
For the evaluation method, the reference standards are complex and various and are difficult to unify, the adaptability is low when the coking coals of different types are detected and analyzed, and most coking coals are qualitatively evaluated, so that when the business operation is executed for the coking coals, the financial and labor costs are high and the resource utilization rate of the coking coals is low due to the lack of objective and comprehensive quantitative analysis results of the coking coals as reference data.
Disclosure of Invention
The embodiment of the invention provides a coking coal business operation method, a coking coal business operation device, computer equipment and a storage medium, and aims to solve the problem that quantitative analysis data cannot accurately guide coking coal business operation due to single index.
In a first aspect, an embodiment of the present invention provides a coking coal service operation method, where the method includes:
detecting a plurality of indicators related to quality at least in the dimension of coking;
calculating a total mass value characterizing mass in at least the dimension of coking from the plurality of indicators for the coking coal;
calculating the cost performance of the coking coal relative to metallurgical behavior according to the total mass value;
and executing business operation on the coking coal according to the cost performance ratio.
Optionally, the coking coal detecting a plurality of indicators relating to quality, at least in the dimension of coking, including:
and (3) detecting at least dry-based ash, dry-ashless-based volatile matter, dry-based total sulfur, a caking index, a colloidal layer thickness and a heat strength of the coking coal as a plurality of indexes related to quality, wherein the heat strength is related to coking property.
Optionally, said calculating an overall mass value characterizing mass in at least a coking dimension for said coking coal from a plurality of said indicators comprises:
calculating a first sub-quality value characterizing quality for the coking coal based on the dry basis ash;
calculating a second sub-quality value characterizing a quality of the coking coal based on the dry ashless-based volatiles;
calculating a third sub-quality value characterizing quality for the coking coal based on the dry-based total sulfur;
calculating a fourth sub-quality value characterizing quality for the coking coal based on the caking index;
calculating a fifth sub-quality value characterizing quality for the coking coal based on the gum layer thickness;
calculating a sixth sub-quality value characterizing quality for the coking coal based on the heat intensity;
and linearly fusing the first sub-mass value, the second sub-mass value, the third sub-mass value, the fourth sub-mass value, the fifth sub-mass value and the sixth sub-mass value to obtain the total mass value of the coking coal.
Optionally, said calculating a first sub-quality value characterizing quality for said coking coal based on said dry basis ash comprises:
if the dry basis ash content is less than 9, calculating a first sub-mass value characterizing mass for the coking coal by the following formula:
100+27+ (9-Ad) × 20, wherein Ad is dry basis ash;
if the dry ash is greater than or equal to 9 and less than 10.5, calculating a first sub-quality value characterizing quality for the coking coal by the following formula:
100+ (10.5-Ad) × 18, wherein Ad is dry basis ash;
if the dry base ash is greater than or equal to 10.5, calculating a first sub-quality value characterizing quality for the coking coal by the following formula:
100+ (10.5-Ad) × 20, wherein Ad is dry basis ash;
said calculating a second sub-quality value indicative of a quality for said coking coal based on said dry ashless-based volatiles, comprising:
setting a second sub-quality value of a characterized quality to the coking coal of 100 if the dry ashless-based volatile content is less than 22.5;
if the absolute value of the difference between the dry ashless-based volatile matter and 22.5 is less than 2.5, a second sub-mass value characterizing mass is calculated for the coking coal by the following equation:
100-ABS (Vdaf-22.5) × 5, wherein Vdaf is a dry ashless based volatile;
if the absolute value of the difference between the dry ashless-based volatile matter and 22.5 is greater than or equal to 2.5, then a second sub-mass value characterizing mass is calculated for the coking coal by the equation:
100-ABS (Vdaf-22.5) × 10, wherein Vdaf is dry ashless based volatile and ABS represents absolute value;
said calculating a third sub-quality value characterizing quality for said coking coal based on said dry-based total sulfur, comprising:
if the dry basis total sulfur distribution is less than 0.6, calculating a third sub-quality value of the characterizing quality for the coking coal by the following formula:
100+32+ (0.6-Std)/0.1 x 12, wherein Std is dry-based total sulfur;
if the dry basis total sulfur is greater than or equal to 0.6 and less than 1, calculating a third sub-mass value characterizing mass for the coking coal by the following formula:
100+ (1-Std)/0.1 x 8, wherein Std is dry-based total sulfur;
if the dry basis total sulfur is greater than or equal to 1 and less than 1.8, calculating a third sub-mass value characterizing mass for the coking coal by the following formula:
100+ (1-Std)/0.1 x 10, wherein Std is dry-based total sulfur;
if the dry basis total sulfur is greater than or equal to 1.8, calculating a third sub-mass value characterizing mass for the coking coal by the following formula:
100-80+ (1.8-Std)/0.1 x 12, wherein Std is dry-based total sulfur;
said calculating a fourth sub-quality value characterizing quality of said coking coal based on said caking index comprising:
if the caking index is greater than 85, calculating a fourth sub-quality value of the characterizing quality for the coking coal by the following formula:
100+15+ (G-85) × 2, wherein G is the sticking index;
if the caking index is less than or equal to 85, calculating a fourth sub-quality value of the characterized quality for the coking coal by the following formula:
100+ (G-80) × 3, wherein G is the sticking index;
calculating a fifth sub-quality value characterizing quality of the coking coal based on the gum layer thickness, comprising:
if the thickness of the colloidal layer is larger than 18, calculating a fifth sub-quality value of the characterization quality for the coking coal by the following formula:
100+8.4+ (Y-18) × 1, wherein Y is the thickness of the colloidal layer;
if the thickness of the colloidal layer is less than or equal to 18, calculating a fifth sub-quality value of the characteristic quality of the coking coal by the following formula:
100+ (Y-15) × 2.8, wherein Y is the thickness of the colloidal layer;
the calculating a sixth sub-quality value characterizing quality of the coking coal based on the heat intensity comprises:
if the heat intensity is empty, setting a sixth sub-quality value representing quality as 100 for the coking coal;
if the heat intensity is not null, calculating a sixth sub-quality value characterizing quality for the coking coal by the following formula:
100+ (CSR-55)/1 x 5, wherein CSR is heat intensity.
Optionally, the linearly fusing the first sub-mass value, the second sub-mass value, the third sub-mass value, the fourth sub-mass value, the fifth sub-mass value and the sixth sub-mass value to obtain the total mass value of the coking coal includes:
configuring a first weight for the dry ash, a second weight for the dry ashless-based volatile matter, a third weight for the dry total sulfur, a fourth weight for the caking index, a fifth weight for the colloidal layer thickness, and a sixth weight for the heat intensity, the sixth weights being all greater than the first weight, the second weight, the third weight, the fourth weight, and the fifth weight;
calculating a first product between the first sub-quality value and the first weight for the dry basis ash;
calculating a second product between the second sub-quality value and the second weight for the dry ashless-based volatiles;
calculating a third product between the third sub-quality value and the third weight for the dry basis total sulfur;
calculating a fourth product between the fourth sub-quality value and the fourth weight for the stickiness index;
calculating a fifth product between the fifth sub-quality value and the fifth weight for the colloidal layer thickness;
calculating a sixth product between the sixth sub-quality value and the sixth weight for the heat intensity;
calculating a sum value between the first product, the second product, the third product, the fourth product, the fifth product, and the sixth product as an overall quality value of the coking coal.
Optionally, the calculating a cost performance of the coking coal relative to metallurgical behavior according to the total mass value includes:
querying a price at which the coking coal is purchased for a metallurgical action;
and taking the ratio of the total quality value to the price as the cost performance of the coking coal relative to metallurgical behaviors.
Optionally, the performing business operations on the coking coal according to the cost performance ratio includes:
comparing the cost performance of the coking coal belonging to a first type with the cost performance of the coking coal belonging to a second type;
and if the cost performance of the coking coal belonging to the first type is higher than that of the coking coal belonging to the second type, generating prompt information for the coking coal belonging to the second type, wherein the prompt information is used for prompting to reduce the price of purchasing the coking coal belonging to the second type.
In a second aspect, an embodiment of the present invention further provides a coking coal service operation apparatus, where the apparatus includes:
the index detection module is used for detecting a plurality of indexes related to quality at least under the dimension of coking property on the coking coal;
the total quality value calculation module is used for calculating a total quality value representing quality at least under the coking dimension for the coking coal according to a plurality of indexes;
the cost performance calculation module is used for calculating the cost performance of the coking coal relative to the metallurgical behavior according to the total mass value;
and the business operation execution module is used for executing business operation on the coking coal according to the cost performance comparison.
Optionally, the index detecting module includes:
and the multiple index detection submodule is used for detecting at least dry-based ash, dry ashless-based volatile matter, dry-based total sulfur, a bonding index, a colloid layer thickness and heat intensity of the coking coal as multiple indexes related to quality, wherein the heat intensity is related to coking property.
Optionally, the total quality value calculation module includes:
a first sub-mass value calculation sub-module for calculating a first sub-mass value characterizing mass for the coking coal based on the dry basis ash;
a second sub-mass value calculation sub-module for calculating a second sub-mass value characterizing mass for the coking coal based on the dry ashless-based volatiles;
a third sub-quality value calculation sub-module for calculating a third sub-quality value characterizing quality of the coking coal based on the dry-based total sulfur;
a fourth sub-quality value calculation sub-module for calculating a fourth sub-quality value characterizing quality of the coking coal based on the caking index;
the fifth sub-quality value calculation submodule is used for calculating a fifth sub-quality value of the characterization quality of the coking coal based on the thickness of the colloidal layer;
a sixth sub-quality value calculation sub-module for calculating a sixth sub-quality value characterizing quality of the coking coal based on the heat intensity;
and the linear fusion submodule is used for performing linear fusion on the first sub-quality value, the second sub-quality value, the third sub-quality value, the fourth sub-quality value, the fifth sub-quality value and the sixth sub-quality value to obtain the total quality value of the coking coal.
Optionally, the first sub-quality value calculation sub-module includes:
a first condition calculation unit for calculating a first sub-mass value characterizing mass for the coking coal by the following formula if the dry basis ash is less than 9:
100+27+ (9-Ad) × 20, wherein Ad is dry basis ash;
a second condition calculation unit for calculating a first sub-quality value of the characterizing quality for the coking coal by the following formula if the number of basic ashes is greater than or equal to 9 and less than 10.5:
100+ (10.5-Ad) × 18, wherein Ad is dry basis ash;
a third condition calculating unit for calculating a first sub-quality value characterizing quality for the coking coal by the following formula if the number of basic ashes is greater than or equal to 10.5:
100+ (10.5-Ad) × 20, wherein Ad is dry basis ash;
the second sub-quality value calculation sub-module includes:
a fourth condition calculation unit for setting a second sub-quality value of characterizing quality to the coking coal of 100 if the dry ashless-based volatile matter is equal to 22.5;
a fifth condition calculation unit for calculating a second sub-quality value characterizing quality for the coking coal if the absolute value of the difference between the dry ashless volatiles and 22.5 is less than 2.5 by the equation:
100-ABS (Vdaf-22.5) × 5, wherein Vdaf is a dry ashless based volatile;
a sixth condition calculating unit for calculating a second sub-mass value of the characterized mass for the coking coal if the absolute value of the difference between the dry ashless volatiles and 22.5 is greater than or equal to 2.5 by the equation:
100-ABS (Vdaf-22.5) × 10, wherein Vdaf is dry ashless based volatile and ABS represents absolute value;
the third sub-quality value calculation sub-module includes:
a seventh condition calculating unit for calculating a third sub-quality value of the characterizing quality for the coking coal by the following formula if the number of the basis total sulfur distributions is less than 0.6:
100+32+ (0.6-Std)/0.1 x 12, wherein Std is dry-based total sulfur;
an eighth condition calculating unit for calculating a third sub-quality value representing quality for the coking coal by the following formula if the dry basis total sulfur is greater than or equal to 0.6 and less than 1:
100+ (1-Std)/0.1 x 8, wherein Std is dry-based total sulfur;
a ninth condition calculating unit for calculating a third sub-quality value of the characterizing quality for the coking coal by the following formula if the total sulfur on a basis is greater than or equal to 1 and less than 1.8:
100+ (1-Std)/0.1 x 10, wherein Std is dry-based total sulfur;
a tenth condition calculation unit for calculating a third sub-quality value characterizing quality for the coking coal by the following formula if the total sulfur on a basis is greater than or equal to 1.8:
100-80+ (1.8-Std)/0.1 x 12, wherein Std is dry-based total sulfur;
the fourth sub-quality value calculation sub-module includes:
an eleventh condition calculating unit for calculating a fourth sub-quality value of the characterizing quality for the coking coal by the following formula if the caking index is greater than 85:
100+15+ (G-85) × 2, wherein G is the sticking index;
a twelfth condition calculation unit for calculating a fourth sub-quality value of the characterizing quality for the coking coal by the following formula if the caking index is less than or equal to 85:
100+ (G-80) × 3, wherein G is the sticking index;
the fifth sub-quality value calculation sub-module includes:
a thirteenth condition calculation unit, configured to calculate a fifth sub-quality value of the characterizing quality for the coking coal according to the following formula if the thickness of the colloidal layer is greater than 18:
100+8.4+ (Y-18) × 1, wherein Y is the thickness of the colloidal layer;
a fourteenth condition calculating unit, configured to calculate a fifth sub-quality value of the characterizing quality for the coking coal by the following formula if the thickness of the colloidal layer is less than or equal to 18:
100+ (Y-15) × 2.8, wherein Y is the thickness of the colloidal layer;
the sixth sub-quality value calculation sub-module includes:
a fifteenth condition calculation unit configured to set a sixth sub-quality value representing quality of 100 for the coking coal if the heat intensity is empty;
a sixteenth condition calculation unit for calculating a sixth sub-quality value representing quality for the coking coal by the following formula if the heat intensity is not empty:
100+ (CSR-55)/1 x 5, wherein CSR is heat intensity.
Optionally, the linear fusion submodule includes:
a weight arrangement unit configured to arrange a first weight for the dry ash, a second weight for the dry ashless volatile matter, a third weight for the dry total sulfur, a fourth weight for the caking index, a fifth weight for the colloidal layer thickness, and a sixth weight for the heat intensity, the sixth weights being each greater than the first weight, the second weight, the third weight, the fourth weight, and the fifth weight;
a first product calculation unit for calculating a first product between the first sub-quality value and the first weight for the dry-based ashes;
a second product calculation unit for calculating a second product between the second sub-quality value and the second weight for the dry ashless-based volatiles;
a third product calculation unit for calculating a third product between the third sub-quality value and the third weight for the dry basis total sulfur;
a fourth product calculation unit for calculating a fourth product between the fourth sub-quality value and the fourth weight for the sticking index;
a fifth product calculation unit, configured to calculate, for the colloidal layer thickness, a fifth product between the fifth sub-quality value and the fifth weight;
a sixth product calculation unit configured to calculate a sixth product between the sixth sub-quality value and the sixth weight for the heat intensity;
and a sum value calculation unit for calculating a sum value between the first product, the second product, the third product, the fourth product, the fifth product and the sixth product as a total quality value of the coking coal.
Optionally, the cost performance calculating module includes:
the price inquiry submodule is used for inquiring the price for purchasing the coking coal for metallurgical behavior;
and the ratio calculation submodule is used for taking the ratio between the total quality value and the price as the cost performance of the coking coal relative to metallurgical behaviors.
Optionally, the service operation execution module includes:
a cost performance comparison submodule for comparing the cost performance of the coking coal belonging to the first type with the cost performance of the coking coal belonging to the second type;
and the prompt information generation submodule is used for generating prompt information for the coking coal belonging to the second type if the cost performance of the coking coal belonging to the first type is higher than that of the coking coal belonging to the second type, and the prompt information is used for prompting to reduce the price of purchasing the coking coal belonging to the second type.
In a third aspect, an embodiment of the present invention further provides a computer device, where the computer device includes:
one or more processors;
a memory for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors implement the method for evaluating coke cost performance according to the first aspect.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the method for evaluating cost performance of coking coal according to the first aspect is implemented.
In the embodiment, a plurality of indexes related to quality at least in the coking dimension are detected for coking coal, a total quality value representing quality at least in the coking dimension is calculated according to the indexes, and the total quality value of coking coal obtained in the coking dimension can comprehensively reflect the quality of coking coal by combining the characteristic of strong coking property of coking coal, so that the reliability of reference data for guiding the coking coal business operation is improved; the cost performance of the coking coal relative to the metallurgical behavior is calculated according to the total quality value, the coking coal is compared according to the performance price ratio to execute the business operation, the operability and the adaptability of the metallurgical behavior performed according to the coking coal cost performance are enhanced, the accuracy of the business operation executed aiming at the coking coal is improved, the financial and labor costs of screening and purchasing the coking coal are reduced, various coking coals can be reasonably utilized, and the possibility of improving the resource utilization rate of the coking coal is increased.
Drawings
Fig. 1 is a flowchart of a coking coal service operation method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a coking coal service operation device according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a computer device according to a third embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of a coking coal business operation method according to an embodiment of the present invention, where this embodiment is applicable to a situation where the cost performance of coking coal is evaluated according to multiple quality indexes and purchase prices of coking coal, and the method may be executed by a coking coal cost performance evaluation device, where the coking coal cost performance evaluation device may be implemented by software and/or hardware, and may be configured in computer equipment, such as a computer, a server, and the like, and specifically includes the following steps:
step 101, a plurality of quality-related indicators at least in the coking dimension are detected for the coking coal.
In this embodiment, at least the following indicators can be detected for the coking coal: dry basis ash content, dry ash-free basis volatile matter, dry basis total sulfur, bonding index, colloid layer thickness and heat strength, and taking the detected indexes as a plurality of indexes related to quality. The heat intensity is related to coking property, and generally, the higher the heat intensity is, the better the coking property of the coking coal is.
Step 102, calculating a total mass value representing mass at least in the dimension of coking property according to a plurality of indexes.
After obtaining the plurality of indicators for the coking coal, an overall mass value for the coking coal may be calculated from the plurality of indicators, the overall mass value being used to characterize the quality of the coking coal in at least the coking dimension. Specifically, the sub-quality values for each indicator may be calculated, and the total quality value may be derived based on each sub-quality value.
In this embodiment, step 102 specifically includes the following steps:
step 1021, calculating a first sub-quality value characterizing quality for the coking coal based on the dry basis ash.
In this embodiment, a first sub-quality value of the characterizing quality may be calculated for the coking coal based on the indicator dry-based ash.
In one example, if the number of base ashes is less than 9, then a first sub-quality value characterizing quality may be calculated for the coking coal by the following equation: 100+27+ (9-Ad) × 20; if the number of base ashes is greater than or equal to 9 and less than 10.5, then a first sub-quality value characterizing quality may be calculated for the coking coal by the following equation: 100+ (10.5-Ad) × 18; if the number of base ashes is greater than or equal to 10.5, then a first sub-quality value characterizing quality may be calculated for the coking coal by the following equation: 100+ (10.5-Ad). 20. It should be noted that all of Ad in the above formula represents dry basis ash.
Step 1022, calculating a second sub-quality value characterizing quality of the coking coal based on the dry ashless-based volatile matter.
In this embodiment, a second sub-mass characterizing the mass may be calculated for the coking coal based on the indicator dry ashless-based volatiles.
In one example, if the number of dry ash-based volatiles is less than 22.5, then a second sub-quality value for the representative quality of the focused coal may be set to 100; if the absolute value of the difference between the dry ash-free basis volatiles and 22.5 is less than 2.5, then a second sub-mass value indicative of mass may be calculated for the coking coal by the following equation: 100-ABS (Vdaf-22.5) × 5; if the absolute value of the difference between the dry ashless-based volatile matter and 22.5 is greater than or equal to 2.5, a second sub-mass value indicative of mass may be calculated for coking coal by the following equation: 100-ABS (Vdaf-22.5) × 10. In the two formulas, Vdaf is a dry ash-free base volatile component; ABS means absolute value.
And 1023, calculating a third sub-quality value of the characterizing quality based on the dry basis total sulfur coking coal.
In this embodiment, a third sub-quality value of the characterized quality may be calculated for the coking coal based on the indicator dry-based total sulfur.
In one example, if the number of basal total sulfur distributions is less than 0.6, then a third sub-quality value characterizing quality may be calculated for the coking coal by the following equation: 100+32+ (0.6-Std)/0.1 x 12; if the total sulfur per radical is greater than or equal to 0.6 and less than 1, a third sub-mass value characterizing the mass can be calculated for the coking coal by the following formula: 100+ (1-Std)/0.1 x 8; if the total sulfur per basis is greater than or equal to 1 and less than 1.8, a third sub-mass value characterizing the mass can be calculated for the coking coal by the following formula: 100+ (1-Std)/0.1 x 10; if the total sulfur is greater than or equal to 1.8 on a basis, a third sub-mass value characterizing the mass may be calculated for the coking coal by the following equation: 100-80+ (1.8-Std)/0.1 x 12. In the above four formulae, Std is dry-based total sulfur.
Step 1024, calculating a fourth sub-quality value of the characterizing quality for the coking coal based on the caking index.
In this embodiment, a fourth sub-quality value of the characterized quality may be calculated for the coking coal based on the index of caking.
In one example, if the caking index is greater than 85, a fourth sub-quality value characterizing the quality may be calculated for the coking coal by the following equation: 100+15+ (G-85) × 2; if the caking index is less than or equal to 85, a fourth sub-quality value of the characterized quality can be calculated for the coking coal by the following formula: 100+ (G-80) × 3. It should be noted that G in the above two formulas is a bonding index.
And 1025, calculating a fifth sub-quality value of the characterization quality of the coking coal based on the thickness of the colloidal layer.
In this embodiment, a fifth sub-quality value of the characterized quality may be calculated for the coking coal based on the indicator colloidal layer thickness.
In one example, if the gum layer thickness is greater than 18, a fifth sub-quality value characterizing quality may be calculated for the coking coal by the following equation: 100+8.4+ (Y-18) × 1; if the gum layer thickness is less than or equal to 18, a fifth sub-quality value characterizing the quality can be calculated for the coking coal by equation 100+ (Y-15) × 2.8. It should be noted that Y in the above two formulas is the thickness of the colloidal layer.
Step 1026, calculating a sixth sub-quality value characterizing the quality based on the thermal intensity focused coal.
In this embodiment, a sixth sub-quality value characterizing quality may be calculated for the coking coal based on the indicative heat intensity, wherein the heat intensity is correlated to coking of the coking coal.
Specifically, in one example, if the heat intensity is empty, a sixth sub-quality value of the characterizing quality of 100 is set for the coking coal; if the heat intensity is not null, a sixth sub-quality value characterizing the quality is calculated for the coking coal by the following formula: 100+ (CSR-55)/1 x 5, wherein CSR is heat intensity.
And step 1027, performing linear fusion on the first sub-mass value, the second sub-mass value, the third sub-mass value, the fourth sub-mass value, the fifth sub-mass value and the sixth sub-mass value to obtain a total mass value of the coking coal.
In this embodiment, the sub-mass values calculated for each index of the coking coal may be linearly fused to obtain the total mass value of the coking coal, and specifically, the first sub-mass value calculated based on the dry ash content, the second sub-mass value calculated based on the dry ash-free volatile matter, the third sub-mass value calculated based on the dry total sulfur, the fourth sub-mass value calculated based on the caking index, the fifth sub-mass value calculated based on the colloidal layer thickness, and the sixth sub-mass value calculated based on the thermal strength may be linearly fused to obtain the total mass value of the coking coal.
In the linear integration, weights may be assigned to the respective indexes, that is, a first weight may be assigned to the dry ash, a second weight may be assigned to the dry ash-free volatile matter, a third weight may be assigned to the dry sulfur-free volatile matter, a fourth weight may be assigned to the caking index, a fifth weight may be assigned to the thickness of the colloidal layer, and a sixth weight may be assigned to the heat intensity, wherein the sixth weights are all greater than the first weight, the second weight, the third weight, the fourth weight, and the fifth weight.
After the weights are configured, a product between the sub-quality values of each indicator and the weights may be calculated. In particular, a first product between a first sub-quality value and a first weight may be calculated for dry basis ash; a second product between a second sub-quality value and a second weight may be calculated for dry ashless-based volatiles; a third product between the third sub-quality value and the third weight may be calculated for dry basis total sulfur; for a caking index, a fourth product between a fourth sub-quality value and a fourth weight may be calculated; for the gum layer thickness, a fifth product between the fifth sub-quality value and the fifth weight may be calculated; for the thermal intensity, a sixth product between a sixth sub-quality value and a sixth weight may be calculated.
Further, the total quality value of the coking coal may be obtained by calculating a sum value between the first product, the second product, the third product, the fourth product, the fifth product, and the sixth product.
Illustratively, the first mass value of dry-based ash is denoted as a1, the first weight is b 1; a second mass value of dry ashless based volatiles denoted a2 and a second weight b 2; a third mass value of dry basis total sulfur is represented by a3 and a third weight is b 3; a fourth quality value of the caking index is denoted as a4, a fourth weight is b 4; the fifth mass value of the thickness of the colloidal layer is represented as a5 and the fifth weight is b 5; a sixth mass value of the heat intensity is represented by a6 and a sixth weight is b 6; the total mass value of the coking coal is represented by Q, and Q is a1 × b1+ a2 × b2+ a3 × b3+ a4 × b4+ a5 × b5+ a6 × b 6.
In practice, the first weight is generally set to 0.17, the second weight is set to 0.18, the third weight is set to 0.13, the fourth weight is set to 0.18, the fifth weight is set to 0.14, and the sixth weight is set to 0.20, but it is needless to say that the sixth weight may be set to be larger than the other weights, though it is sufficient to ensure that the sixth weight is larger than the other weights.
And 103, calculating the cost performance of the coking coal relative to the metallurgical behavior according to the total mass value.
At the time of purchasing the coking coal, the type, price, and the like of the coking coal are recorded and stored, and therefore, in the present embodiment, the price for purchasing the coking coal for the metallurgical action can be obtained by querying in the history.
The cost performance is the ratio of the performance value to the price value of the commodity, and is a quantitative measuring mode for reflecting the purchasable degree of the commodity. In this embodiment, the cost performance of the coking coal relative to the metallurgical behavior can be obtained by calculating the ratio between the total mass value and the price.
For example, Q represents the total quality value of the coking coal, P represents the price of the purchased coking coal, and the cost performance T of the coking coal is Q/P.
And 104, executing business operation on the coking coal according to the cost performance.
In the purchasing process, a plurality of coking coals may exist, and the quality and the price of different coking coals are different, so that the cost performance is different. The business operations can be performed on the coking coal according to the cost performance in the embodiment.
Since the cost performance of the coking coal is related to the quality and price of the coking coal, and the quality of the coking coal is a fixed characteristic of the coking coal and cannot be easily changed by human operation, in the embodiment, the executable business operation includes adjusting the price of the coking coal at the time of purchase.
In one example, the cost performance of the coking coal belonging to the first type may be compared to the cost performance of the coking coal belonging to the second type, and if the cost performance of the coking coal belonging to the first type is higher than the cost performance of the coking coal belonging to the second type, a prompt for reducing the price for purchasing the coking coal belonging to the second type is generated for the coking coal belonging to the second type,
it should be noted that, in addition to adjusting the price of purchased coking coal according to the cost performance ratio of coking coal, the business operation performed in this embodiment may also sequence coking coal according to the total quality value of coking coal, so as to instruct which types of coking coal are used to perform metallurgical actions, so as to reduce the coking cost.
In the embodiment, a plurality of indexes related to quality at least in the coking dimension are detected for coking coal, a total quality value representing quality at least in the coking dimension is calculated according to the indexes, and the total quality value of coking coal obtained in the coking dimension can comprehensively reflect the quality of coking coal by combining the characteristic of strong coking property of coking coal, so that the reliability of reference data for guiding the coking coal business operation is improved; the cost performance of the coking coal relative to the metallurgical behavior is calculated according to the total quality value, the coking coal is compared according to the performance price ratio to execute the business operation, the operability and the adaptability of the metallurgical behavior performed according to the coking coal cost performance are enhanced, the accuracy of the business operation executed aiming at the coking coal is improved, the financial and labor costs of screening and purchasing the coking coal are reduced, various coking coals can be reasonably utilized, and the possibility of improving the resource utilization rate of the coking coal is increased.
It should be noted that, for simplicity of description, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the illustrated order of acts, as some steps may occur in other orders or concurrently in accordance with the embodiments of the present invention. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred and that no particular act is required to implement the invention.
Example two
Fig. 2 is a block diagram of a coking coal service operation device according to a second embodiment of the present invention, which may specifically include the following modules:
an index detection module 201, configured to detect a plurality of indexes related to quality of the coking coal at least in a coking dimension;
a total mass value calculation module 202 for calculating a total mass value characterizing mass in at least the coking dimension for the coking coal based on the plurality of indicators;
the cost performance calculation module 203 is used for calculating the cost performance of the coking coal relative to the metallurgical behavior according to the total mass value;
and the business operation execution module 204 is used for executing business operation on the coking coal according to the cost performance ratio.
In an embodiment of the present invention, the index detecting module 201 includes:
and the multiple index detection submodule is used for detecting at least dry-based ash, dry ashless-based volatile matter, dry-based total sulfur, a bonding index, a colloid layer thickness and heat intensity of the coking coal as multiple indexes related to quality, wherein the heat intensity is related to coking property.
In an embodiment of the present invention, the total quality value calculation module 202 includes:
a first sub-mass value calculation sub-module for calculating a first sub-mass value characterizing mass for the coking coal based on the dry basis ash;
a second sub-mass value calculation sub-module for calculating a second sub-mass value characterizing mass for the coking coal based on the dry ashless-based volatiles;
a third sub-quality value calculation sub-module for calculating a third sub-quality value characterizing quality of the coking coal based on the dry-based total sulfur;
a fourth sub-quality value calculation sub-module for calculating a fourth sub-quality value characterizing quality of the coking coal based on the caking index;
the fifth sub-quality value calculation submodule is used for calculating a fifth sub-quality value of the characterization quality of the coking coal based on the thickness of the colloidal layer;
a sixth sub-quality value calculation sub-module for calculating a sixth sub-quality value characterizing quality of the coking coal based on the heat intensity;
and the linear fusion submodule is used for performing linear fusion on the first sub-quality value, the second sub-quality value, the third sub-quality value, the fourth sub-quality value, the fifth sub-quality value and the sixth sub-quality value to obtain the total quality value of the coking coal.
In one embodiment of the present invention, the first sub-quality value calculation sub-module includes:
a first condition calculation unit for calculating a first sub-mass value characterizing mass for the coking coal by the following formula if the dry basis ash is less than 9:
100+27+ (9-Ad) × 20, wherein Ad is dry basis ash;
a second condition calculation unit for calculating a first sub-quality value of the characterizing quality for the coking coal by the following formula if the number of basic ashes is greater than or equal to 9 and less than 10.5:
100+ (10.5-Ad) × 18, wherein Ad is dry basis ash;
a third condition calculating unit for calculating a first sub-quality value characterizing quality for the coking coal by the following formula if the number of basic ashes is greater than or equal to 10.5:
100+ (10.5-Ad) × 20, wherein Ad is dry basis ash;
the second sub-quality value calculation sub-module includes:
a fourth condition calculation unit for setting a second sub-quality value of characterizing quality to the coking coal of 100 if the dry ashless-based volatile matter is equal to 22.5;
a fifth condition calculation unit for calculating a second sub-quality value characterizing quality for the coking coal if the absolute value of the difference between the dry ashless volatiles and 22.5 is less than 2.5 by the equation:
100-ABS (Vdaf-22.5) × 5, wherein Vdaf is a dry ashless based volatile;
a sixth condition calculating unit for calculating a second sub-mass value of the characterized mass for the coking coal if the absolute value of the difference between the dry ashless volatiles and 22.5 is greater than or equal to 2.5 by the equation:
100-ABS (Vdaf-22.5) × 10, wherein Vdaf is dry ashless based volatile and ABS represents absolute value;
the third sub-quality value calculation sub-module includes:
a seventh condition calculating unit for calculating a third sub-quality value of the characterizing quality for the coking coal by the following formula if the number of the basis total sulfur distributions is less than 0.6:
100+32+ (0.6-Std)/0.1 x 12, wherein Std is dry-based total sulfur;
an eighth condition calculating unit for calculating a third sub-quality value representing quality for the coking coal by the following formula if the dry basis total sulfur is greater than or equal to 0.6 and less than 1:
100+ (1-Std)/0.1 x 8, wherein Std is dry-based total sulfur;
a ninth condition calculating unit for calculating a third sub-quality value of the characterizing quality for the coking coal by the following formula if the total sulfur on a basis is greater than or equal to 1 and less than 1.8:
100+ (1-Std)/0.1 x 10, wherein Std is dry-based total sulfur;
a tenth condition calculation unit for calculating a third sub-quality value characterizing quality for the coking coal by the following formula if the total sulfur on a basis is greater than or equal to 1.8:
100-80+ (1.8-Std)/0.1 x 12, wherein Std is dry-based total sulfur;
the fourth sub-quality value calculation sub-module includes:
an eleventh condition calculating unit for calculating a fourth sub-quality value of the characterizing quality for the coking coal by the following formula if the caking index is greater than 85:
100+15+ (G-85) × 2, wherein G is the sticking index;
a twelfth condition calculation unit for calculating a fourth sub-quality value of the characterizing quality for the coking coal by the following formula if the caking index is less than or equal to 85:
100+ (G-80) × 3, wherein G is the sticking index;
the fifth sub-quality value calculation sub-module includes:
a thirteenth condition calculation unit, configured to calculate a fifth sub-quality value of the characterizing quality for the coking coal according to the following formula if the thickness of the colloidal layer is greater than 18:
100+8.4+ (Y-18) × 1, wherein Y is the thickness of the colloidal layer;
a fourteenth condition calculating unit, configured to calculate a fifth sub-quality value of the characterizing quality for the coking coal by the following formula if the thickness of the colloidal layer is less than or equal to 18:
100+ (Y-15) × 2.8, wherein Y is the thickness of the colloidal layer;
the sixth sub-quality value calculation sub-module includes:
a fifteenth condition calculation unit configured to set a sixth sub-quality value representing quality of 100 for the coking coal if the heat intensity is empty;
a sixteenth condition calculation unit for calculating a sixth sub-quality value representing quality for the coking coal by the following formula if the heat intensity is not empty:
100+ (CSR-55)/1 x 5, wherein CSR is heat intensity.
In one embodiment of the present invention, the linear fusion submodule includes:
a weight arrangement unit configured to arrange a first weight for the dry ash, a second weight for the dry ashless volatile matter, a third weight for the dry total sulfur, a fourth weight for the caking index, a fifth weight for the colloidal layer thickness, and a sixth weight for the heat intensity, the sixth weights being each greater than the first weight, the second weight, the third weight, the fourth weight, and the fifth weight;
a first product calculation unit for calculating a first product between the first sub-quality value and the first weight for the dry-based ashes;
a second product calculation unit for calculating a second product between the second sub-quality value and the second weight for the dry ashless-based volatiles;
a third product calculation unit for calculating a third product between the third sub-quality value and the third weight for the dry basis total sulfur;
a fourth product calculation unit for calculating a fourth product between the fourth sub-quality value and the fourth weight for the sticking index;
a fifth product calculation unit, configured to calculate, for the colloidal layer thickness, a fifth product between the fifth sub-quality value and the fifth weight;
a sixth product calculation unit configured to calculate a sixth product between the sixth sub-quality value and the sixth weight for the heat intensity;
and a sum value calculation unit for calculating a sum value between the first product, the second product, the third product, the fourth product, the fifth product and the sixth product as a total quality value of the coking coal.
In an embodiment of the present invention, the cost performance calculating module 203 includes:
the price inquiry submodule is used for inquiring the price for purchasing the coking coal for metallurgical behavior;
and the ratio calculation submodule is used for taking the ratio between the total quality value and the price as the cost performance of the coking coal relative to metallurgical behaviors.
In an embodiment of the present invention, the business operation executing module 204 includes:
a cost performance comparison submodule for comparing the cost performance of the coking coal belonging to the first type with the cost performance of the coking coal belonging to the second type;
and the prompt information generation submodule is used for generating prompt information for the coking coal belonging to the second type if the cost performance of the coking coal belonging to the first type is higher than that of the coking coal belonging to the second type, and the prompt information is used for prompting to reduce the price of purchasing the coking coal belonging to the second type.
The coking coal cost performance evaluation device provided by the embodiment of the invention can execute the coking coal cost performance evaluation method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
EXAMPLE III
Fig. 3 is a schematic structural diagram of a computer device according to a third embodiment of the present invention. FIG. 3 illustrates a block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention. The computer device 12 shown in FIG. 3 is only an example and should not impose any limitation on the scope of use or functionality of embodiments of the present invention.
As shown in FIG. 3, computer device 12 is in the form of a general purpose computing device. The components of computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Computer device 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. Computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 3, and commonly referred to as a "hard drive"). Although not shown in FIG. 3, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
Computer device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with computer device 12, and/or with any devices (e.g., network card, modem, etc.) that enable computer device 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. Also, computer device 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via network adapter 20. As shown, network adapter 20 communicates with the other modules of computer device 12 via bus 18. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with computer device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, to implement the method for evaluating the cost performance of coking coal according to the embodiment of the present invention.
Example four
The fourth embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the coking coal cost performance evaluation method, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here.
A computer readable storage medium may include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims (10)

1. A coking coal service operation method, comprising:
detecting a plurality of indicators related to quality at least in the dimension of coking;
calculating a total mass value characterizing mass in at least the dimension of coking from the plurality of indicators for the coking coal;
calculating the cost performance of the coking coal relative to metallurgical behavior according to the total mass value;
and executing business operation on the coking coal according to the cost performance ratio.
2. The method of claim 1, wherein the coking coal detecting a plurality of indicators related to quality in at least the dimension of coking, comprises:
and (3) detecting at least dry-based ash, dry-ashless-based volatile matter, dry-based total sulfur, a caking index, a colloidal layer thickness and a heat strength of the coking coal as a plurality of indexes related to quality, wherein the heat strength is related to coking property.
3. The method of claim 2, wherein said calculating an overall mass value characterizing mass in at least a coking dimension for said coking coal from a plurality of said indicators comprises:
calculating a first sub-quality value characterizing quality for the coking coal based on the dry basis ash;
calculating a second sub-quality value characterizing a quality of the coking coal based on the dry ashless-based volatiles;
calculating a third sub-quality value characterizing quality for the coking coal based on the dry-based total sulfur;
calculating a fourth sub-quality value characterizing quality for the coking coal based on the caking index;
calculating a fifth sub-quality value characterizing quality for the coking coal based on the gum layer thickness;
calculating a sixth sub-quality value characterizing quality for the coking coal based on the heat intensity;
and linearly fusing the first sub-mass value, the second sub-mass value, the third sub-mass value, the fourth sub-mass value, the fifth sub-mass value and the sixth sub-mass value to obtain the total mass value of the coking coal.
4. The method of claim 3,
the calculating a first sub-quality value characterizing quality for the coking coal based on the dry basis ash comprises:
if the dry basis ash content is less than 9, calculating a first sub-mass value characterizing mass for the coking coal by the following formula:
100+27+ (9-Ad) × 20, wherein Ad is dry basis ash;
if the dry ash is greater than or equal to 9 and less than 10.5, calculating a first sub-quality value characterizing quality for the coking coal by the following formula:
100+ (10.5-Ad) × 18, wherein Ad is dry basis ash;
if the dry base ash is greater than or equal to 10.5, calculating a first sub-quality value characterizing quality for the coking coal by the following formula:
100+ (10.5-Ad) × 20, wherein Ad is dry basis ash;
said calculating a second sub-quality value indicative of a quality for said coking coal based on said dry ashless-based volatiles, comprising:
setting a second sub-quality value of a characterized quality to the coking coal of 100 if the dry ashless-based volatile content is less than 22.5;
if the absolute value of the difference between the dry ashless-based volatile matter and 22.5 is less than 2.5, a second sub-mass value characterizing mass is calculated for the coking coal by the following equation:
100-ABS (Vdaf-22.5) × 5, wherein Vdaf is a dry ashless based volatile;
if the absolute value of the difference between the dry ashless-based volatile matter and 22.5 is greater than or equal to 2.5, then a second sub-mass value characterizing mass is calculated for the coking coal by the equation:
100-ABS (Vdaf-22.5) × 10, wherein Vdaf is dry ashless based volatile and ABS represents absolute value;
said calculating a third sub-quality value characterizing quality for said coking coal based on said dry-based total sulfur, comprising:
if the dry basis total sulfur distribution is less than 0.6, calculating a third sub-quality value of the characterizing quality for the coking coal by the following formula:
100+32+ (0.6-Std)/0.1 x 12, wherein Std is dry-based total sulfur;
if the dry basis total sulfur is greater than or equal to 0.6 and less than 1, calculating a third sub-mass value characterizing mass for the coking coal by the following formula:
100+ (1-Std)/0.1 x 8, wherein Std is dry-based total sulfur;
if the dry basis total sulfur is greater than or equal to 1 and less than 1.8, calculating a third sub-mass value characterizing mass for the coking coal by the following formula:
100+ (1-Std)/0.1 x 10, wherein Std is dry-based total sulfur;
if the dry basis total sulfur is greater than or equal to 1.8, calculating a third sub-mass value characterizing mass for the coking coal by the following formula:
100-80+ (1.8-Std)/0.1 x 12, wherein Std is dry-based total sulfur;
said calculating a fourth sub-quality value characterizing quality of said coking coal based on said caking index comprising:
if the caking index is greater than 85, calculating a fourth sub-quality value of the characterizing quality for the coking coal by the following formula:
100+15+ (G-85) × 2, wherein G is the sticking index;
if the caking index is less than or equal to 85, calculating a fourth sub-quality value of the characterized quality for the coking coal by the following formula:
100+ (G-80) × 3, wherein G is the sticking index;
calculating a fifth sub-quality value characterizing quality of the coking coal based on the gum layer thickness, comprising:
if the thickness of the colloidal layer is larger than 18, calculating a fifth sub-quality value of the characterization quality for the coking coal by the following formula:
100+8.4+ (Y-18) × 1, wherein Y is the thickness of the colloidal layer;
if the thickness of the colloidal layer is less than or equal to 18, calculating a fifth sub-quality value of the characteristic quality of the coking coal by the following formula:
100+ (Y-15) × 2.8, wherein Y is the thickness of the colloidal layer;
the calculating a sixth sub-quality value characterizing quality of the coking coal based on the heat intensity comprises:
if the heat intensity is empty, setting a sixth sub-quality value representing quality as 100 for the coking coal;
if the heat intensity is not null, calculating a sixth sub-quality value characterizing quality for the coking coal by the following formula:
100+ (CSR-55)/1 x 5, wherein CSR is heat intensity.
5. The method of claim 3, wherein linearly fusing the first, second, third, fourth, fifth, and sixth sub-quality values to obtain an overall quality value for the coking coal comprises:
configuring a first weight for the dry ash, a second weight for the dry ashless-based volatile matter, a third weight for the dry total sulfur, a fourth weight for the caking index, a fifth weight for the colloidal layer thickness, and a sixth weight for the heat intensity, the sixth weights being all greater than the first weight, the second weight, the third weight, the fourth weight, and the fifth weight;
calculating a first product between the first sub-quality value and the first weight for the dry basis ash;
calculating a second product between the second sub-quality value and the second weight for the dry ashless-based volatiles;
calculating a third product between the third sub-quality value and the third weight for the dry basis total sulfur;
calculating a fourth product between the fourth sub-quality value and the fourth weight for the stickiness index;
calculating a fifth product between the fifth sub-quality value and the fifth weight for the colloidal layer thickness;
calculating a sixth product between the sixth sub-quality value and the sixth weight for the heat intensity;
calculating a sum value between the first product, the second product, the third product, the fourth product, the fifth product, and the sixth product as an overall quality value of the coking coal.
6. The method of any one of claims 1 to 5, wherein calculating the cost/performance ratio of the coking coal with respect to metallurgical behavior based on the total mass value comprises:
querying a price at which the coking coal is purchased for a metallurgical action;
and taking the ratio of the total quality value to the price as the cost performance of the coking coal relative to metallurgical behaviors.
7. The method of claim 6, wherein the performing business operations on the coking coal according to the cost-effective ratio comprises:
comparing the cost performance of the coking coal belonging to a first type with the cost performance of the coking coal belonging to a second type;
and if the cost performance of the coking coal belonging to the first type is higher than that of the coking coal belonging to the second type, generating prompt information for the coking coal belonging to the second type, wherein the prompt information is used for prompting to reduce the price of purchasing the coking coal belonging to the second type.
8. A coking coal service operation apparatus, comprising:
the index detection module is used for detecting a plurality of indexes related to quality at least under the dimension of coking property on the coking coal;
the total quality value calculation module is used for calculating a total quality value representing quality at least under the coking dimension for the coking coal according to a plurality of indexes;
the cost performance calculation module is used for calculating the cost performance of the coking coal relative to the metallurgical behavior according to the total mass value;
and the business operation execution module is used for executing business operation on the coking coal according to the cost performance comparison.
9. A computer device, characterized in that the computer device comprises:
one or more processors;
a memory for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the coking coal cost performance evaluation method of any one of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the coking coal cost performance evaluation method according to any one of claims 1 to 7.
CN202110129866.2A 2021-01-29 2021-01-29 Coking coal business operation method, device computer equipment and storage medium Pending CN112907042A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110129866.2A CN112907042A (en) 2021-01-29 2021-01-29 Coking coal business operation method, device computer equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110129866.2A CN112907042A (en) 2021-01-29 2021-01-29 Coking coal business operation method, device computer equipment and storage medium

Publications (1)

Publication Number Publication Date
CN112907042A true CN112907042A (en) 2021-06-04

Family

ID=76121678

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110129866.2A Pending CN112907042A (en) 2021-01-29 2021-01-29 Coking coal business operation method, device computer equipment and storage medium

Country Status (1)

Country Link
CN (1) CN112907042A (en)

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
RU2009131270A (en) * 2009-08-17 2011-02-27 Открытое акционерное общество "Западно-Сибирский металлургический комбинат" (RU) METHOD FOR DETERMINING THE OPTIMAL COMPOSITION OF COAL MIXTURE FOR COKING
CN102901802A (en) * 2012-10-12 2013-01-30 江苏沙钢集团有限公司 Method for evaluating cost performance of coking coal
CN105062531A (en) * 2015-08-12 2015-11-18 中钢集团鞍山热能研究院有限公司 Coking raw material applicability classification, comprehensive quality evaluation and coal blending guiding method
KR20160072665A (en) * 2014-12-15 2016-06-23 주식회사 포스코 Method for sample quality prediction and Method for forecasting CSR(Coke Strength Reaction)
CN110275007A (en) * 2019-06-12 2019-09-24 邯郸钢铁集团有限责任公司 A kind of method for building up of coking coal cost performance evaluation model

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
RU2009131270A (en) * 2009-08-17 2011-02-27 Открытое акционерное общество "Западно-Сибирский металлургический комбинат" (RU) METHOD FOR DETERMINING THE OPTIMAL COMPOSITION OF COAL MIXTURE FOR COKING
CN102901802A (en) * 2012-10-12 2013-01-30 江苏沙钢集团有限公司 Method for evaluating cost performance of coking coal
KR20160072665A (en) * 2014-12-15 2016-06-23 주식회사 포스코 Method for sample quality prediction and Method for forecasting CSR(Coke Strength Reaction)
CN105062531A (en) * 2015-08-12 2015-11-18 中钢集团鞍山热能研究院有限公司 Coking raw material applicability classification, comprehensive quality evaluation and coal blending guiding method
CN110275007A (en) * 2019-06-12 2019-09-24 邯郸钢铁集团有限责任公司 A kind of method for building up of coking coal cost performance evaluation model

Similar Documents

Publication Publication Date Title
US10489283B2 (en) Software defect reporting
US9588820B2 (en) Cloud architecture recommender system using automated workload instrumentation
Theisen et al. Approximating attack surfaces with stack traces
CN106021045B (en) The test method of server hard disc IO performance under a kind of Linux system
CN103166989A (en) Resource use metering method and resource use metering system for cloud computing
EP2686771B1 (en) Usability testing
CN101283347A (en) Expert system analysis and graphical display of privilege elevation pathways in a computing environment
CN106169124B (en) System-level product reliability comprehensive evaluation confidence inference method
US20140089479A1 (en) Management of system events using one or more event attributes
Kaur et al. A COSMIC function points based test effort estimation model for mobile applications
US20060095312A1 (en) Method, system, and storage medium for using comparisons of empirical system data for testcase and workload profiling
JP2018147280A (en) Data analysis device and data analysis method
Rosa et al. Early phase cost models for agile software processes in the US DoD
CN113822693A (en) Method, device, equipment and storage medium for generating user purchasing power evaluation value
CN112907042A (en) Coking coal business operation method, device computer equipment and storage medium
US20080162273A1 (en) System and method of tracking process for managing decisions
KR101611433B1 (en) Performance testing method, performance testing apparatus performing the same and storage media sotring the same
CN111127223A (en) Insurance product testing method and device and storage medium
US7668680B2 (en) Operational qualification by independent reanalysis of data reduction patch
CN115130130A (en) Network disk file unlocking method and device, network disk and storage medium
Gu et al. Evaluation measures about software V&V of the safety digital I&C system in nuclear power plant
CN109348236B (en) Storage capacity evaluation method and device, server and storage medium
TWI733017B (en) Test estimation apparatus and method thereof
CN110555687A (en) method, server and user side for associating transaction account
CN110806981A (en) Application program testing method, device, equipment and storage medium

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