CN112501368B - Blast furnace smelting method and computer equipment - Google Patents
Blast furnace smelting method and computer equipment Download PDFInfo
- Publication number
- CN112501368B CN112501368B CN202011288552.9A CN202011288552A CN112501368B CN 112501368 B CN112501368 B CN 112501368B CN 202011288552 A CN202011288552 A CN 202011288552A CN 112501368 B CN112501368 B CN 112501368B
- Authority
- CN
- China
- Prior art keywords
- blast furnace
- furnace
- tuyere
- information
- blast
- 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.)
- Active
Links
Classifications
-
- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21B—MANUFACTURE OF IRON OR STEEL
- C21B5/00—Making pig-iron in the blast furnace
- C21B5/006—Automatically controlling the process
-
- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21B—MANUFACTURE OF IRON OR STEEL
- C21B2300/00—Process aspects
- C21B2300/04—Modeling of the process, e.g. for control purposes; CII
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Manufacturing & Machinery (AREA)
- Materials Engineering (AREA)
- Metallurgy (AREA)
- Organic Chemistry (AREA)
- Manufacture Of Iron (AREA)
- Waste-Gas Treatment And Other Accessory Devices For Furnaces (AREA)
Abstract
The invention relates to the technical field of blast furnace smelting, and discloses a blast furnace smelting method and computer equipment, wherein the method comprises the following steps: step S1: acquiring a data set comprising historical production conditions of the blast furnace and corresponding blast furnace tuyere image information, and fitting according to the data set to obtain a relational expression of the production conditions, the blast furnace tuyere image information and the furnace temperature; step S2: obtaining the current furnace temperature through the relational expression in the step S1 according to the current blast furnace production condition and the corresponding blast furnace tuyere image information; step S3: and making a blast furnace production decision according to the current furnace temperature. According to the blast furnace smelting method, the relational expression of the production conditions, the blast furnace tuyere image information and the furnace temperature is obtained through fitting, so that the furnace temperature of the blast furnace can be obtained through calculation according to the input production conditions and the monitored blast furnace tuyere image information, the monitoring of the thermal state of the blast furnace is realized, and the furnace condition of the blast furnace is further adjusted in real time.
Description
Technical Field
The invention relates to the technical field of blast furnace metallurgy, in particular to a blast furnace smelting method and computer equipment.
Background
Blast furnace smelting is a process of reducing iron ore to iron and discharging it. Iron ore, coke and flux are fed into the blast furnace from the top of the blast furnace in batches, and high-temperature oxygen-enriched hot air is blown into the lower part of the blast furnace to spray coal powder. The coke and the coal powder are combusted at the tuyere to generate reducing gas which flows upwards, and the ore is gradually reduced and heated to be molten into molten iron and slag in the descending process, and finally discharged from the blast furnace.
The stable production of qualified molten iron is the goal of blast furnace production and control, and the thermal state is an important factor affecting the stability of the blast furnace and the quality of the molten iron, so that the important task of a blast furnace operator is to maintain the stability of the thermal state of the blast furnace during the operation process. To maintain the thermal state of the blast furnace stable, the thermal state of the blast furnace must be monitored. In the prior production operation process, an operator usually knows the thermal state of the blast furnace by monitoring the temperature and the silicon content of the discharged molten iron, but the method belongs to post monitoring, and the monitoring result can only be used as a reference for adjusting the furnace condition because the condition in the furnace cannot be reflected in time.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, an object of the present invention is to provide a blast furnace smelting method, which can monitor the thermal state of a blast furnace and further adjust the condition of the blast furnace in real time.
The inventor finds that the direct reduction reaction amount in the blast furnace is a main branch of the heat of the lower part of the blast furnace, the change of the direct reduction reaction amount has great influence on the change of the heat of the lower part of the blast furnace, the change of the direct reduction reaction amount is often the most important factor influencing the stability of the blast furnace, and the change can be measured by the direct reduction degree of the blast furnace. Secondly, the inventor found that in the prior blast furnace production process, experienced blast furnace operators can judge the thermal state of the blast furnace by observing the brightness of the tuyere by naked eyes, and then the blast furnace operation is adjusted according to the judgment.
Therefore, in order to achieve the purpose, the invention provides a blast furnace smelting method, which comprises the following steps:
step S1: acquiring a data set comprising historical production conditions of the blast furnace and corresponding blast furnace tuyere image information, and fitting according to the data set to obtain a relational expression of the production conditions, the blast furnace tuyere image information and the furnace temperature;
step S2: obtaining the current furnace temperature through the relational expression in the step S1 according to the current blast furnace production condition and the corresponding blast furnace tuyere image information;
step S3: and making a blast furnace production decision according to the current furnace temperature.
Further, the step S1 specifically includes:
acquiring a data set comprising the historical production conditions of the blast furnace and corresponding blast furnace tuyere image information;
calculating blast furnace parameters in a historical production process according to historical production conditions in the data set, and extracting historical tuyere image brightness information from the blast furnace tuyere image information in the data set;
and fitting a relation among blast furnace parameters, historical tuyere image brightness information and furnace temperature in the historical production process through an algorithm.
Further, the production conditions comprise air blowing conditions, raw fuel conditions, coal gas conditions, heat loss conditions, historical molten iron temperature and molten iron silicon content information; the blast furnace parameters comprise direct reduction degree, heat loss amount and blast heat.
Further, the extraction of the tuyere image brightness information comprises the following steps:
setting a calculation period;
collecting a plurality of tuyere images at the same time interval in a calculation period;
and averaging the tuyere image information in a calculation period to generate an average image, and extracting a green brightness mean value of the average image, namely the tuyere image brightness information.
Further, the relation among the blast furnace parameters, the tuyere brightness information and the furnace temperature is as follows:
Si＝a×(h2-h1-q×r1)+b×m+c
wherein Si represents the silicon content of the molten iron and is used for representing the furnace temperature; a. b and q are coefficients, c is a constant term, r1 represents the direct reduction degree, h1 represents the heat loss amount, h2 represents the blowing heat amount, and m represents the green brightness average value.
Further, the relation among the blast furnace parameters, the tuyere brightness information and the furnace temperature is as follows:
Si＝a×q×r1+b×m+c
wherein Si represents the silicon content of the molten iron and is used for representing the furnace temperature; a. b and q are coefficients, c is a constant term, r1 represents the direct reduction degree, and m represents the mean value of green brightness.
The invention also provides computer equipment, which comprises an input unit, an image processing unit, a fitting algorithm unit and an execution unit;
the input unit is used for inputting production condition information and tuyere images of the blast furnace;
the image processing unit is used for analyzing the input air opening image and acquiring air opening image brightness information;
the algorithm unit is used for fitting a relational expression of production conditions, blast furnace tuyere image information and furnace temperature; obtaining the current furnace temperature through a relational expression according to the current blast furnace production condition and the corresponding blast furnace tuyere image information;
and the execution unit is used for generating blast furnace production decision information according to the current furnace temperature.
The invention realizes the following technical effects:
according to the blast furnace smelting method, the relational expression of the production conditions, the blast furnace tuyere image information and the furnace temperature is obtained through fitting, so that the furnace temperature of the blast furnace can be obtained through calculation according to the input production conditions and the monitored blast furnace tuyere image information, the monitoring of the thermal state of the blast furnace is realized, and the furnace condition of the blast furnace is further adjusted in real time.
Detailed Description
The invention discloses a blast furnace smelting method for monitoring the thermal state of a blast furnace in real time, which comprises the following steps:
step S1: obtaining a large amount of historical production conditions of the blast furnace and corresponding blast furnace tuyere image information, and obtaining a relational expression of the production conditions, the blast furnace tuyere image information and the furnace temperature through fitting.
Step S2: acquiring a data set comprising historical production conditions of the blast furnace and corresponding blast furnace tuyere image information, and fitting according to the data set to obtain a relational expression of the production conditions, the blast furnace tuyere image information and the furnace temperature;
step S3: and making a blast furnace production decision according to the current furnace temperature.
Further, the step S1 specifically includes:
acquiring a data set comprising the historical production conditions of the blast furnace and corresponding blast furnace tuyere image information;
calculating blast furnace parameters in a historical production process according to historical production conditions in the data set, and extracting historical tuyere image brightness information according to the blast furnace tuyere image information in the data set;
and fitting a relation among blast furnace parameters, historical tuyere image brightness information and furnace temperature in the historical production process through an algorithm.
Wherein the production conditions comprise air blowing conditions, raw fuel conditions, coal gas conditions, heat loss conditions, historical molten iron temperature and molten iron silicon content information; the blast furnace parameters comprise direct reduction degree, heat loss amount and blast heat.
Further, the extraction of the tuyere image brightness information comprises the following steps:
(1) setting a calculation period;
(2) collecting a plurality of tuyere images at the same time interval in a calculation period;
(3) and averaging the tuyere image information in a calculation period to generate an average image, and extracting a green brightness mean value of the average image, namely the tuyere image brightness information. The color of the extracted average image depends on the color in the tuyere image information, which is used for representing the furnace temperature, and in the present embodiment, the color is green.
For example: the calculation period is divided into 10 equal parts by taking 5 minutes as a calculation period, one image is acquired at the same time (such as the starting time or the ending time) of each equal part, and 10 images are acquired in total at each tuyere in one calculation period.
Calculating the direct reduction degree, the heat loss amount and the blast heat;
extracting air opening image brightness information: carrying out average processing on 10 pieces of image information of each air port in the same calculation period to generate 1 piece of average image, and extracting green brightness mean value information of the average image;
and recording the direct reduction degree, the heat loss amount, the air blowing heat and the green brightness mean value information in a database.
In one embodiment, the relationship among the blast furnace parameters, tuyere brightness information and furnace temperature can be obtained by a curve fitting algorithm as follows:
Si＝a×(h2-h1-q×r1)+b×m+c
wherein Si represents the silicon content of the molten iron and is used for representing the furnace temperature; a. b and q are coefficients, c is a constant term, r1 represents the direct reduction degree, h1 represents the heat loss amount, h2 represents the blowing heat amount, and m represents the green brightness average value.
Wherein, the direct reduction degree can be obtained by calculating the ratio of the direct reduced iron amount to the total reduced iron amount;
the heat loss can be obtained through the temperature difference information between the cooling water quantity and the cooling water of the furnace body;
the blast heat can be obtained by blast temperature and blast quantity.
In another embodiment, the relationship among the blast furnace parameters, the tuyere brightness information and the furnace temperature can be obtained by a curve fitting algorithm as follows:
Si＝a×q×r1+b×m+c
wherein Si represents the silicon content of the molten iron and is used for representing the furnace temperature; a. b and q are coefficients, c is a constant term, r1 represents the direct reduction degree, and m represents the mean value of green brightness.
Wherein the direct reduction degree can be obtained by calculating the ratio of the amount of direct reduced iron to the amount of the total reduced iron.
According to the blast furnace smelting method, the relational expression of the production conditions, the blast furnace tuyere image information and the furnace temperature is obtained through fitting, so that the furnace temperature of the blast furnace can be obtained through calculation according to the input production conditions and the monitored blast furnace tuyere image information, the monitoring of the thermal state of the blast furnace is realized, and the furnace condition of the blast furnace is further adjusted in real time.
The invention also provides computer equipment which comprises functional modules such as an input unit, an image processing unit, a fitting algorithm unit, an execution unit and the like. The input unit is a data interface and is used for inputting production condition information and tuyere images of the blast furnace; the image processing unit is used for analyzing the input air opening image and acquiring air opening image brightness information; the algorithm unit is used for fitting a relational expression of the production conditions, the blast furnace tuyere image information and the furnace temperature; obtaining the current furnace temperature through a relational expression according to the current blast furnace production condition and the corresponding blast furnace tuyere image information; and the execution unit is used for generating blast furnace production decision information according to the current furnace temperature. The image processing unit, the algorithm unit and the execution unit are computer programs, and the computer programs are stored in nonvolatile storage media of the computer equipment, such as storage media of a mechanical hard disk, a solid state hard disk, an onboard flash memory and the like; the computer program is loaded into at least one processor unit of the computer apparatus for execution and performs a blast furnace process as described below.
While the invention has been particularly shown and described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (4)
1. A blast furnace smelting method is characterized by comprising the following steps:
step S1: acquiring a data set comprising historical production conditions of the blast furnace and corresponding blast furnace tuyere image information, and fitting according to the data set to obtain a relational expression of the production conditions, the blast furnace tuyere image information and the furnace temperature;
step S2: obtaining the current furnace temperature through the relational expression in the step S1 according to the current blast furnace production condition and the corresponding blast furnace tuyere image information;
step S3: making a blast furnace production decision according to the current furnace temperature;
the step S1 specifically includes:
acquiring a data set comprising the historical production conditions of the blast furnace and the corresponding blast furnace tuyere image information;
calculating blast furnace parameters in a historical production process according to historical production conditions in the data set, and extracting historical tuyere image brightness information according to the blast furnace tuyere image information in the data set;
fitting a relation among blast furnace parameters, historical tuyere image brightness information and furnace temperature in a historical production process through an algorithm;
the relational expression of the blast furnace parameters, the tuyere image brightness information and the furnace temperature is as follows:
Si＝a×(h2-h1-q×r1)+b×m+c
wherein Si represents the silicon content of the molten iron and is used for representing the furnace temperature; a. b and q are coefficients, c is a constant term, r1 represents the direct reduction degree, h1 represents the heat loss amount, h2 represents the blast heat amount, and m represents the average value of green brightness;
or is represented as:
Si＝a×q×r1+b×m+c
wherein Si represents the silicon content of the molten iron and is used for representing the furnace temperature; a. b and q are coefficients, c is a constant term, r1 represents the direct reduction degree, and m represents the mean value of the green brightness.
2. The blast furnace smelting method according to claim 1, wherein the production conditions include blast conditions, raw fuel conditions, gas conditions, heat loss conditions, historical molten iron temperature, and molten iron silicon content information; the blast furnace parameters comprise the direct reduction degree, the heat loss amount and the blast heat.
3. The blast furnace smelting method according to claim 1, wherein the extraction of the tuyere image brightness information comprises the steps of:
setting a calculation period;
collecting a plurality of tuyere images at the same time interval in a calculation period;
and averaging the tuyere image information in a calculation period to generate an average image, and extracting a green brightness mean value of the average image, namely the tuyere image brightness information.
4. A computer device is characterized by comprising an input unit, an image processing unit, a fitting algorithm unit and an execution unit;
the input unit is used for inputting production condition information and tuyere images of the blast furnace;
the image processing unit is used for analyzing the input air opening image and acquiring air opening image brightness information;
the algorithm unit is used for fitting a relational expression of production conditions, blast furnace tuyere image information and furnace temperature; obtaining the current furnace temperature through a relational expression according to the current blast furnace production condition and the corresponding blast furnace tuyere image information;
the execution unit is used for generating blast furnace production decision information according to the current furnace temperature;
the relational expression of the blast furnace parameters, the tuyere image brightness information and the furnace temperature is as follows:
Si＝a×(h2-h1-q×r1)+b×m+c
wherein Si represents the silicon content of the molten iron and is used for representing the furnace temperature; a. b and q are coefficients, c is a constant term, r1 represents the direct reduction degree, h1 represents the heat loss amount, h2 represents the blast heat amount, and m represents the average value of green brightness;
or is represented as:
Si＝a×q×r1+b×m+c
wherein Si represents the silicon content of the molten iron and is used for representing the furnace temperature; a. b and q are coefficients, c is a constant term, r1 represents the direct reduction degree, and m represents the mean value of green brightness.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011288552.9A CN112501368B (en) | 2020-11-17 | 2020-11-17 | Blast furnace smelting method and computer equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011288552.9A CN112501368B (en) | 2020-11-17 | 2020-11-17 | Blast furnace smelting method and computer equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112501368A CN112501368A (en) | 2021-03-16 |
| CN112501368B true CN112501368B (en) | 2022-07-08 |
Family
ID=74956577
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011288552.9A Active CN112501368B (en) | 2020-11-17 | 2020-11-17 | Blast furnace smelting method and computer equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112501368B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116459731B (en) * | 2023-04-20 | 2024-01-09 | 深圳市正泰隆科技有限公司 | Automatic aluminum alloy batching data processing method and system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103509902A (en) * | 2013-09-25 | 2014-01-15 | 马钢(集团)控股有限公司 | Video and temperature monitoring device and method for blast-furnace tuyere |
| CN104498654A (en) * | 2014-12-29 | 2015-04-08 | 燕山大学 | Blast furnace temperature change trend determination method and device |
| CN105392904A (en) * | 2013-07-29 | 2016-03-09 | 杰富意钢铁株式会社 | Abnormality detection method and blast-furnace operation method |
| KR20190078319A (en) * | 2017-12-26 | 2019-07-04 | 주식회사 포스코 | System and method of evaluating furnace operation state |
-
2020
- 2020-11-17 CN CN202011288552.9A patent/CN112501368B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105392904A (en) * | 2013-07-29 | 2016-03-09 | 杰富意钢铁株式会社 | Abnormality detection method and blast-furnace operation method |
| CN103509902A (en) * | 2013-09-25 | 2014-01-15 | 马钢(集团)控股有限公司 | Video and temperature monitoring device and method for blast-furnace tuyere |
| CN104498654A (en) * | 2014-12-29 | 2015-04-08 | 燕山大学 | Blast furnace temperature change trend determination method and device |
| KR20190078319A (en) * | 2017-12-26 | 2019-07-04 | 주식회사 포스코 | System and method of evaluating furnace operation state |
Non-Patent Citations (2)
| Title |
|---|
| 基于高炉数据与风口图像的炉温综合预测;陈智辉;《中国优秀博硕士学位论文全文数据库(硕士)工程科技Ⅰ辑》;20150815;"3.2.2 图像灰度值确定"；"3.4 基于风口图像的炉温预测"；"4.2变量选择及相关性分析"；"结论"部分 * |
| 基于高炉数据与风口图像的炉温预测;崔桂梅等;《工程科学学报》;20151231;第37卷;第155-160页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112501368A (en) | 2021-03-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111593155B (en) | Blast furnace diagnosis system and method | |
| CN111607673B (en) | Pre-iron diagnostic system and method | |
| CN112501368B (en) | Blast furnace smelting method and computer equipment | |
| CN104392213B (en) | A kind of image information state recognition system suitable for fusion process | |
| JP7107444B2 (en) | Hot metal temperature control method, operation guidance method, blast furnace operation method, hot metal manufacturing method, hot metal temperature control device, and operation guidance device | |
| CN112465223A (en) | Blast furnace temperature state prediction method | |
| JP6687080B2 (en) | Molten metal temperature correction device, molten metal temperature correction method, and molten metal manufacturing method | |
| CN110628981A (en) | Solidification experience method for defining splashing in converter blowing period | |
| JP2017066510A (en) | Molten iron temperature calculation method in blast furnace | |
| CN115386664A (en) | Method for improving temperature uniformity of tuyere by adjusting flow of pulverized coal branch pipe of blast furnace | |
| CN114065526A (en) | Self-adaptive optimized safety control system for steelmaking blast furnace | |
| CN113255741A (en) | Thermal image tracking and control method for high-temperature smelting soft stirring system | |
| CN109750133B (en) | Evaporative cooler water spray amount control method and device based on modeling | |
| CN113962152A (en) | Method for calculating reactivity and post-reaction strength of alkali-rich coke in high-titanium blast furnace | |
| CN111270028B (en) | Coping method and coping system for converting dry quenching into wet quenching of blast furnace | |
| Lyalyuk et al. | Uniformity of blast-furnace parameters over the perimeter | |
| CN115341069A (en) | Molten steel carbon content prediction control method of converter blowing end point based on online dynamic detection model | |
| JP2021123795A (en) | Static blowing control method, temperature correction term estimation device, and converter control device | |
| JP7193032B1 (en) | Supplied heat amount estimation method, supplied heat amount estimation device, and blast furnace operation method | |
| CN118879968A (en) | Method for judging slag-entering point of steelmaking by utilizing gas in converter | |
| CN109609720A (en) | Converter dry dedusting micro-differential pressure control method and device and converter dry dedusting system | |
| JP7524861B2 (en) | Static blowing control method, temperature correction term/oxygen correction term estimation device, and converter control device | |
| RU2817694C1 (en) | Refining process control device and refining process control method | |
| JP7156560B2 (en) | Refining process control device and refining process control method | |
| TWI417757B (en) | System and method for evaluating coke quality |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |