EP3712281B1 - Blast control device for blast furnace and method therefor - Google Patents
Blast control device for blast furnace and method therefor Download PDFInfo
- Publication number
- EP3712281B1 EP3712281B1 EP18879916.7A EP18879916A EP3712281B1 EP 3712281 B1 EP3712281 B1 EP 3712281B1 EP 18879916 A EP18879916 A EP 18879916A EP 3712281 B1 EP3712281 B1 EP 3712281B1
- Authority
- EP
- European Patent Office
- Prior art keywords
- blast
- blast furnace
- particle size
- data
- volume
- 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
- 238000000034 method Methods 0.000 title claims description 20
- 239000002245 particle Substances 0.000 claims description 45
- 230000035699 permeability Effects 0.000 claims description 25
- 239000000463 material Substances 0.000 claims description 24
- 238000003384 imaging method Methods 0.000 claims description 9
- 238000013528 artificial neural network Methods 0.000 claims description 7
- 238000010191 image analysis Methods 0.000 claims description 6
- 230000032258 transport Effects 0.000 claims 2
- 239000007789 gas Substances 0.000 description 15
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 14
- 229910000805 Pig iron Inorganic materials 0.000 description 9
- 239000000446 fuel Substances 0.000 description 8
- 229910052742 iron Inorganic materials 0.000 description 7
- 239000002994 raw material Substances 0.000 description 7
- 230000009467 reduction Effects 0.000 description 7
- 230000008569 process Effects 0.000 description 5
- 239000000571 coke Substances 0.000 description 4
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000012790 confirmation Methods 0.000 description 2
- 239000000470 constituent Substances 0.000 description 2
- 239000001301 oxygen Substances 0.000 description 2
- 229910052760 oxygen Inorganic materials 0.000 description 2
- 239000008188 pellet Substances 0.000 description 2
- 230000000087 stabilizing effect Effects 0.000 description 2
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 description 1
- 229910000831 Steel Inorganic materials 0.000 description 1
- 229910002091 carbon monoxide Inorganic materials 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
- 238000011105 stabilization Methods 0.000 description 1
- 239000010959 steel Substances 0.000 description 1
Images
Classifications
-
- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21B—MANUFACTURE OF IRON OR STEEL
- C21B7/00—Blast furnaces
- C21B7/24—Test rods or other checking devices
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F27—FURNACES; KILNS; OVENS; RETORTS
- F27D—DETAILS OR ACCESSORIES OF FURNACES, KILNS, OVENS, OR RETORTS, IN SO FAR AS THEY ARE OF KINDS OCCURRING IN MORE THAN ONE KIND OF FURNACE
- F27D21/00—Arrangements of monitoring devices; Arrangements of safety devices
- F27D21/0014—Devices for monitoring temperature
-
- 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
- C21B7/00—Blast furnaces
- C21B7/16—Tuyéres
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F27—FURNACES; KILNS; OVENS; RETORTS
- F27B—FURNACES, KILNS, OVENS, OR RETORTS IN GENERAL; OPEN SINTERING OR LIKE APPARATUS
- F27B1/00—Shaft or like vertical or substantially vertical furnaces
- F27B1/10—Details, accessories, or equipment peculiar to furnaces of these types
- F27B1/26—Arrangements of controlling devices
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F27—FURNACES; KILNS; OVENS; RETORTS
- F27B—FURNACES, KILNS, OVENS, OR RETORTS IN GENERAL; OPEN SINTERING OR LIKE APPARATUS
- F27B1/00—Shaft or like vertical or substantially vertical furnaces
- F27B1/10—Details, accessories, or equipment peculiar to furnaces of these types
- F27B1/28—Arrangements of monitoring devices, of indicators, of alarm devices
-
- 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
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F27—FURNACES; KILNS; OVENS; RETORTS
- F27D—DETAILS OR ACCESSORIES OF FURNACES, KILNS, OVENS, OR RETORTS, IN SO FAR AS THEY ARE OF KINDS OCCURRING IN MORE THAN ONE KIND OF FURNACE
- F27D19/00—Arrangements of controlling devices
- F27D2019/0003—Monitoring the temperature or a characteristic of the charge and using it as a controlling value
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F27—FURNACES; KILNS; OVENS; RETORTS
- F27D—DETAILS OR ACCESSORIES OF FURNACES, KILNS, OVENS, OR RETORTS, IN SO FAR AS THEY ARE OF KINDS OCCURRING IN MORE THAN ONE KIND OF FURNACE
- F27D19/00—Arrangements of controlling devices
- F27D2019/0028—Regulation
- F27D2019/0034—Regulation through control of a heating quantity such as fuel, oxidant or intensity of current
- F27D2019/004—Fuel quantity
- F27D2019/0043—Amount of air or O2 to the burner
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F27—FURNACES; KILNS; OVENS; RETORTS
- F27D—DETAILS OR ACCESSORIES OF FURNACES, KILNS, OVENS, OR RETORTS, IN SO FAR AS THEY ARE OF KINDS OCCURRING IN MORE THAN ONE KIND OF FURNACE
- F27D21/00—Arrangements of monitoring devices; Arrangements of safety devices
- F27D2021/0007—Monitoring the pressure
Definitions
- the present invention relates to a device for controlling a blast in a blast furnace and a method thereof.
- pig iron is manufactured by reducing natural iron ore by use of a carbon monoxide produced in reaction of coke that is a fuel and oxygen.
- a condition of a blast furnace From among various operational factors for indicating an inner furnace condition of a blast furnace in a blast furnace process (referred to as a condition of a blast furnace hereinafter), permeability that represents a gas flowing degree in the furnace is one of very important factors for determining efficiency and safety of a blast furnace operation.
- the blast furnace operation is performed when a reduction gas rises in the furnace to contact the charged iron ore, and the iron ore having received heat according to a contact with the reduction gas is fused and reduced into pig iron.
- thermal energy and the reduction gas needed in fusion and reduction of iron ore are supplied by a hot blast supplied through a lower portion of the furnace, and for the purpose of stabilizing the condition of the blast furnace, it is very important to appropriately control an amount of the hot blast input through the lower portion, that is, a blast volume.
- the blast volume supplied into the furnace is controlled according to the permeability in the furnace.
- the volume of pig iron produced in the blast furnace increases, but there may be a stabilization drawback when the blast volume increases while the permeability in the furnace is not good. Therefore, an operator decreases the blast volume so as to stabilize the operation when permeability in the furnace is bad, and increases the blast volume so as to increase operation efficiency when the permeability is good.
- Particle sizes and particle size distribution of raw material (sintered ore, pellets, sized lumps, etc.) fuels (cokes) charged through an upper portion of the blast furnace determine porosity of a charging layer, which is a very important factor for determining permeability at the upper portion in the furnace.
- the present invention has been made in an effort to provide a device for controlling a blast for confirming a particle size and a particle size distribution of a charging material charged into a furnace in real time and controlling a hot-blast volume supplied therein, and a method thereof.
- An aspect of the present invention provides a device for controlling a blast in a blast furnace, as disclosed in appended claim 1.
- the data collector may obtain the particle size and the particle size distribution of the charging material according to an image analysis of the image.
- the device may further include at least one sensor for obtaining at least one piece of sensing data for indicating permeability of the blast furnace, wherein the blast volume predictor may obtain the blast volume predictive value by using the particle size data and the at least one piece of sensing data.
- the blast volume predictive model may output the blast volume predictive value corresponding to the particle size data and the at least one piece of sensing data.
- the blast volume controller may control the hot-blast volume by controlling an opened or closed degree of a blast valve between a hot stove and the blast furnace.
- Another aspect of the present invention provides a method for controlling a blast in a blast furnace, as disclosed in appended claim 5.
- the obtaining of particle size data may include obtaining a particle size and a particle size distribution of the charging material according to an image analysis on the image.
- the method may further include obtaining at least one piece of sensing data for indicating permeability of the blast furnace through at least one sensor, wherein the obtaining of a blast volume predictive value may include obtaining the blast volume predictive value by using the particle size data and the at least one piece of sensing data.
- the at least one piece of sensing data may include a pressure in the blast furnace, a temperature in the blast furnace, or a gas component discharged from the blast furnace.
- the obtaining of a blast volume predictive value may include obtaining the blast volume predictive value by using the particle size data and the at least one piece of sensing data as input data of a blast volume predictive model for estimating a blast volume of the blast furnace.
- the controlling of a hot-blast volume may include controlling the hot-blast volume by controlling an opened or closed degree of a blast valve between a hot stove and the blast furnace.
- the change of the condition of the blast furnace may be minimized, the blast furnace operation may be stabilized, and efficiency may be increased by confirming the particle size and the particle size distribution of the charging material charged into the furnace and accordingly controlling the blast volume.
- an element when it is described that an element is “coupled” to another element, the element may be “directly coupled” to the other element or “electrically coupled” to the other element through a third element.
- FIG. 1 shows an example of blast furnace equipment.
- the blast furnace equipment is for generating pig iron in a steel process.
- the blast furnace 10 is a furnace into which an iron ore that is a raw material is charged and is fused and reduced to pig iron.
- a burden hopper 11 for storing a raw material or fuel charged through a charging conveyor belt 5 is positioned at an upper portion of the blast furnace 10. The raw material or the fuel stored in the burden hopper 11 is charged into the blast furnace 10 according to a burden charging process.
- a blast port 12 for inputting a hot blast supplied by a hot stove 20 into the blast furnace 10 is positioned on a lower portion of the blast furnace 10.
- An inflow amount of the hot blast supplied by the hot stove 20 into the blast furnace 10 (referred to as a blast volume hereinafter) is controlled according to an opened or closed degree of the blast valve 21.
- the fuel (e.g., cokes) input into the blast furnace 10 is combusted in reaction with oxygen to generate high-temperature gas (referred to as reduction gas hereinafter).
- reduction gas rises in the furnace to contact the iron ore charged into the blast furnace 10.
- the iron ore having received heat according to the contact with the high-temperature reduction gas in the furnace is fused and reduced into pig iron.
- the pig iron fused and reduced in the blast furnace 10 is stored at a lower portion of the furnace, and it is then discharged to the outside of the furnace through a tap hole at regular intervals.
- FIG. 2 shows a device for controlling blast in a blast furnace according to an exemplary embodiment of the present invention.
- the device 100 for controlling a blast may include an imaging device 110, a sensor unit 120, a data collector 130, a permeability parameter storage unit 140, a learner 150, a blast volume predictive model database 160, a blast volume predictor 170, a blast volume controller 180, and a display 190.
- the imaging device 110 is installed on a charging conveyor belt 5, and photographs the raw material (sintered ore, pellets, sized lumps, etc.) or the fuel (coke, etc.) charged into the blast furnace 10 by use of the charging conveyor belt 5.
- the image photographed by the imaging device 110 is used to obtain particle size data (particle sizes and particle size distribution) of the charging material (fuel or raw material). Therefore, a high-quality camera may be used as the imaging device 110 so as to enable obtainment of the particle size and the particle size distribution of the charging material from the image on the charging material.
- the sensor unit 120 includes at least one sensor for measuring factors (e.g., a pressure, a temperature, an exhaust gas component, etc.) for determining permeability inside the blast furnace 10.
- factors e.g., a pressure, a temperature, an exhaust gas component, etc.
- the sensor unit 120 may include a temperature sensor 121 for measuring a temperature inside the blast furnace 10.
- the temperature sensor 121 may be attached to the inside of the blast furnace 10, and it may also be positioned outside the blast furnace 10 to measure the temperature when the pig iron discharged from the blast furnace 10 is tapped. In the latter case, the temperature inside the blast furnace 10 may be estimated from the temperature of the pig iron.
- the sensor unit 120 may include a pressure sensor 122 for measuring the pressure inside the blast furnace 10.
- the sensor unit 120 may also include a gas sensor 123 for detecting a component of an exhaust gas (blast furnace gas) discharged by the blast furnace 10.
- a gas sensor 123 for detecting a component of an exhaust gas (blast furnace gas) discharged by the blast furnace 10.
- the data collector 130 may obtain particle size data (particle sizes and particle size distribution) on the charging material charged to the blast furnace 10 through the charging conveyor belt 5 according to real-time image analysis of the image of the charging material obtained by the imaging device 110. Further, the data collector 130 may obtain sensing data (a temperature, a pressure, an exhaust gas component, etc.) measured by the sensor unit 120 as a permeability parameter.
- the permeability parameters (particle size data and sensing data) obtained in this way may be stored in the permeability parameter storage unit 140 as time-series data. They may also be displayed on a blast furnace operating screen through the display 190 so that an operator may confirm a situation in the blast furnace 10 in real time.
- the learner 150 may learn the permeability parameter (particle size data, sensing data) collected by the data collector 130 as learning data for a predetermined time, and may generate a neural-network-algorithm-based blast volume predictive model.
- the learner 150 may make a neural network learn by using collected permeability parameters and blast volume control values proposed by an expert as neural network algorithm learning data, and may produce a blast volume predictive model for predicting the blast volume based on present permeability parameters from learning results.
- the neural network algorithm used in the learning may be configured with a neural network with a plurality of layers.
- the blast volume predictive model produced by the learner 150 is stored in the blast volume predictive model database 160 and is used for the blast volume predictor 170 to predict the blast volume.
- the blast volume predictor 170 may estimate the blast volume of a charging layer inside the blast furnace 10 from the permeability parameters that are time-series data by using a neural-network-algorithm-based blast volume predictive model.
- the blast volume predictor 170 may input the permeability parameters collected by the data collector 130 as time-series input data of the blast volume predictive model, and may obtain an output value of the blast volume predictive model as a corresponding blast volume predictive value.
- the blast volume controller 180 may determine an amount of the hot blast, that is, the blast volume, supplied into the blast furnace 10 based on the blast volume predictive value output by the blast volume predictor 170, and may control an opened or closed degree of the blast valve 21, thereby controlling the blast volume input into the blast furnace 10.
- functions of the data collector 130, the learner 150, the blast volume predictor 170, and the blast volume controller 180 may be performed by a processor realized with at least one central processing unit (CPU), other chipsets, or a microprocessor.
- CPU central processing unit
- other chipsets or a microprocessor.
- FIG. 3 shows a method for controlling a blast in a blast furnace according to an exemplary embodiment of the present invention.
- the device 100 for controlling a blast photographs the charging conveyor belt 5 by using the imaging device 110 to thus capture an image of the charging material (a raw material or fuel) moved to the blast furnace 10 (S100). Particle size data on the charging material are obtained by image analysis of the obtained charging material image (S110).
- the device 100 for controlling a blast obtains sensing data indicating permeability inside the blast furnace 10 through at least one of sensors 121, 122, and 123 (S120).
- the particle size data and the sensing data obtained through the step S110 and the step S120 are stored in the permeability parameter storage unit 140 as permeability parameters.
- the device 100 for controlling a blast continuously obtains the permeability parameters through the step S110 and the step S120, and uses the same as time-series input data of the neural network algorithm based blast volume predictive model to obtain the predictive value of the blast volume in the blast furnace 10 (S130).
- the device 100 for controlling a blast controls the blast volume supplied into the blast furnace 10 by controlling the opened or closed degree of the blast valve 21 based on the obtained blast volume predictive value (S140).
- the device 100 for controlling a blast supports confirmation of the particle size and the particle size distribution of the charging material charged into the blast furnace 10 in real time.
- the device 100 for controlling a blast supports automatic control of the blast volume according to the condition of the blast furnace by providing a predictive model for predicting the blast volume according to the present condition of the blast furnace through learning. Therefore, the device 100 for controlling a blast may control the blast volume in real-time reaction to the condition of the blast furnace, thereby minimizing changes of the condition of the blast furnace and resultantly stabilizing an operation of the blast furnace and increasing efficiency.
- the method for controlling a blast according to an exemplary embodiment of the present invention may be performed by using software.
- configurational tools for the present invention are code segments for performing necessary tasks.
- the program or the code segments may be stored in a computer-readable recording medium.
- Computer-readable recording media include all types of recording apparatuses in which data readable by a computer system are stored. Examples of the computer-readable recording devices include a ROM, a RAM, a CD-ROM, a DVD_ROM, a DVD_RAM, a magnetic tape, a floppy disk, a hard disk drive, and an optical data storage device. Further, the computer-readable recording media may be distributed to a computer device connected by a network, and computer-readable codes may be stored and performed in a distributed fashion.
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- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Manufacturing & Machinery (AREA)
- Materials Engineering (AREA)
- Metallurgy (AREA)
- Organic Chemistry (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Manufacture Of Iron (AREA)
- Blast Furnaces (AREA)
- Waste-Gas Treatment And Other Accessory Devices For Furnaces (AREA)
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
KR1020170151770A KR102002428B1 (ko) | 2017-11-14 | 2017-11-14 | 고로의 송풍 제어 장치 및 그 방법 |
PCT/KR2018/007588 WO2019098484A1 (ko) | 2017-11-14 | 2018-07-04 | 고로의 송풍 제어 장치 및 그 방법 |
Publications (3)
Publication Number | Publication Date |
---|---|
EP3712281A1 EP3712281A1 (en) | 2020-09-23 |
EP3712281A4 EP3712281A4 (en) | 2020-09-23 |
EP3712281B1 true EP3712281B1 (en) | 2023-02-15 |
Family
ID=66538640
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP18879916.7A Active EP3712281B1 (en) | 2017-11-14 | 2018-07-04 | Blast control device for blast furnace and method therefor |
Country Status (5)
Country | Link |
---|---|
EP (1) | EP3712281B1 (ko) |
JP (1) | JP7012159B2 (ko) |
KR (1) | KR102002428B1 (ko) |
CN (1) | CN111344420A (ko) |
WO (1) | WO2019098484A1 (ko) |
Families Citing this family (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR100508379B1 (ko) * | 2002-12-10 | 2005-08-17 | 엔프라니 주식회사 | 주목(朱木) 과육(果肉)으로부터 유래된 폴리사카라이드의제조방법 및 이들을 함유하는 화장료 조성물 |
US20220380859A1 (en) * | 2019-10-31 | 2022-12-01 | Jfe Steel Corporation | Method for operating blast furnace |
JP7380604B2 (ja) * | 2021-01-12 | 2023-11-15 | Jfeスチール株式会社 | 学習モデル生成方法、学習モデル生成装置、高炉の制御ガイダンス方法、及び溶銑の製造方法 |
CN113793308A (zh) * | 2021-08-25 | 2021-12-14 | 北京科技大学 | 一种基于神经网络的球团矿质量智能评级方法及装置 |
Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH02170906A (ja) * | 1988-12-22 | 1990-07-02 | Kawasaki Steel Corp | 高炉送風流量制御方法 |
Family Cites Families (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPS6039724B2 (ja) * | 1977-11-08 | 1985-09-07 | 日本鋼管株式会社 | 高炉炉況判定方法およびその装置 |
JPS5855512A (ja) * | 1981-09-29 | 1983-04-01 | Kawasaki Steel Corp | 高炉の炉況判定方法 |
JPS61147804A (ja) * | 1984-12-18 | 1986-07-05 | Sumitomo Metal Ind Ltd | 高炉操業方法 |
JPS6283410A (ja) * | 1985-10-08 | 1987-04-16 | Sumitomo Metal Ind Ltd | 高炉操業方法 |
JPH0730368B2 (ja) * | 1988-02-12 | 1995-04-05 | 日本鋼管株式会社 | 高炉炉熱制御装置 |
JPH03236409A (ja) * | 1990-02-13 | 1991-10-22 | Nkk Corp | 高炉装入原料の粒度制御方法 |
JPH0598322A (ja) * | 1991-10-02 | 1993-04-20 | Nkk Corp | 高炉装入物の粒度制御方法 |
JP4901462B2 (ja) | 2006-12-27 | 2012-03-21 | 新日本製鐵株式会社 | 炉頂部のガス流状態監視方法、監視装置、及びコンピュータプログラム |
KR101605206B1 (ko) * | 2009-12-21 | 2016-03-21 | 주식회사 포스코 | 고로내 송풍용 열풍온도 제어장치 |
KR101277973B1 (ko) * | 2011-07-28 | 2013-06-27 | 현대제철 주식회사 | 고로의 송풍 에너지 제어 방법 |
GB2509121B (en) * | 2012-12-21 | 2015-03-18 | Siemens Plc | Apparatus for supplying blast to a blast furnace |
KR101466499B1 (ko) * | 2013-07-26 | 2014-11-28 | 현대제철 주식회사 | 연화 융착대 가시화 방법 |
JP6044536B2 (ja) * | 2013-12-27 | 2016-12-14 | Jfeスチール株式会社 | 高炉装入物検出装置 |
CN105177199B (zh) * | 2015-08-31 | 2017-04-19 | 南京南瑞继保电气有限公司 | 高炉煤气发生量软测量方法 |
CN106521066A (zh) * | 2016-12-23 | 2017-03-22 | 天津市三特电子有限公司 | 高炉炉料粒度监控系统及分布数据在线分析方法 |
-
2017
- 2017-11-14 KR KR1020170151770A patent/KR102002428B1/ko active IP Right Grant
-
2018
- 2018-07-04 JP JP2020526586A patent/JP7012159B2/ja active Active
- 2018-07-04 CN CN201880073801.7A patent/CN111344420A/zh active Pending
- 2018-07-04 EP EP18879916.7A patent/EP3712281B1/en active Active
- 2018-07-04 WO PCT/KR2018/007588 patent/WO2019098484A1/ko unknown
Patent Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH02170906A (ja) * | 1988-12-22 | 1990-07-02 | Kawasaki Steel Corp | 高炉送風流量制御方法 |
Also Published As
Publication number | Publication date |
---|---|
JP7012159B2 (ja) | 2022-01-27 |
KR102002428B1 (ko) | 2019-07-22 |
EP3712281A1 (en) | 2020-09-23 |
CN111344420A (zh) | 2020-06-26 |
EP3712281A4 (en) | 2020-09-23 |
WO2019098484A1 (ko) | 2019-05-23 |
JP2021503042A (ja) | 2021-02-04 |
KR20190054794A (ko) | 2019-05-22 |
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