JPH0663009B2 - Blast furnace charge distribution control method - Google Patents
Blast furnace charge distribution control methodInfo
- Publication number
- JPH0663009B2 JPH0663009B2 JP88689A JP88689A JPH0663009B2 JP H0663009 B2 JPH0663009 B2 JP H0663009B2 JP 88689 A JP88689 A JP 88689A JP 88689 A JP88689 A JP 88689A JP H0663009 B2 JPH0663009 B2 JP H0663009B2
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- Japan
- Prior art keywords
- distribution
- charge
- condition
- furnace
- distribution control
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Description
【発明の詳細な説明】 〔産業上の利用分野〕 本発明は高炉の操業方法、特に分布制御方法に関するも
のである。The present invention relates to a method for operating a blast furnace, and more particularly to a distribution control method.
高炉操業は非常に多くの操業因子が相互に関連し合って
成立っているものであり、さらに設備条件等から直接視
覚で炉内を監視する事が困難なため、操業レベルの維持
向上を図るためには高炉に取付けられたセンサー等の情
報を総合的に判断し、的確に制御する必要がある。この
ため現在でも高炉の日常操業管理には操業者の経験や知
識が重要なものとなっている。Blast furnace operation consists of a large number of operation factors that are mutually related, and it is difficult to directly visually monitor the inside of the furnace from the equipment conditions, etc., so the operation level is maintained and improved. In order to do so, it is necessary to comprehensively judge the information from the sensors installed in the blast furnace and to control it appropriately. For this reason, the experience and knowledge of operators are still important for the daily operation management of blast furnaces.
知識工学システムは、このような人間のノウハウを計算
機に取込んで処理する事が出来るため、特開昭62−2707
08号公報及び特開昭62−270712号公報に示されているよ
うな高炉操業管理への知識工学システムの導入が進めら
れている。操業管理のシステム化により、情報の見落し
や判断ミス等の問題が無くなり、操業管理の適正化や標
準化が図られる。Since the knowledge engineering system can take in such human know-how into a computer and process it, there is a problem in Japanese Patent Laid-Open No. 62-2707.
The introduction of a knowledge engineering system for blast furnace operation management as shown in JP-A-08 and JP-A-62-270712 is being promoted. By systematizing operation management, problems such as oversight of information and erroneous judgments will be eliminated, and operation management will be optimized and standardized.
特開昭62−270712号公報に開示されている知識工学シス
テムでは、吹抜けやスリップの予測を行うものである
が、対処方法の出力までは行っていない。高炉の制御ま
で行っているものとして、特開昭62−270708号公報に開
示されている高炉炉熱制御システムがあるが、あくまで
も高炉操業の中の炉熱レベルという項目のみの制御であ
り、高炉操業全体に対処し得るシステムとはなっていな
い。特に日常の高炉操業と安定維持するためには高炉の
操業状況に合わせて木目細かく装入物分布制御を行う必
要がある。炉内のガス流分布がどのような状況になって
いるかを判断するには過去の経験や知識の活用が有効で
あるが、それに対する具体的な分布制御方法に関しては
過去の経験や知識通りにならない事が多い。これは、高
炉の装入物分布制御手段が各装入銘柄の炉内半径装入位
置、１チャージ内の装入銘柄の分割装入方式及び分割装
入量、炉内装入面レベル等多数存在すると共に、同じ制
御方法でもその時の原料粒度構成等の条件により装入物
分布に対する効果が異なるためである。従って、過去の
経験や知識に基づいて構築した知識ベースによる推論
で、その時の最適な装入物分布制御方法を導き出すのは
極めて困難であるという問題があった。The knowledge engineering system disclosed in Japanese Patent Laid-Open No. 62-270712 predicts blow through and slip, but does not output the coping method. There is a blast furnace thermal control system disclosed in Japanese Patent Laid-Open No. 62-270708 as a system for controlling the blast furnace, but it is only control of the item of the furnace heat level in the blast furnace operation. It is not a system that can handle the entire operation. In particular, in order to maintain stable operation with daily blast furnace operation, it is necessary to finely control the distribution of the charge according to the operating conditions of the blast furnace. It is effective to use past experience and knowledge to judge what kind of situation the gas flow distribution in the furnace is, but regarding the specific distribution control method for it, follow the past experience and knowledge. There are many things that do not happen. This is because the charge distribution control means of the blast furnace has a large number of positions such as the inner radius charging position of each charging brand, the divided charging method and the divided charging amount of the charging brand in one charge, the level of the furnace interior surface, etc. In addition, even with the same control method, the effect on the distribution of the charge differs depending on the conditions such as the raw material particle size composition at that time. Therefore, there is a problem that it is extremely difficult to derive an optimal charge distribution control method at that time by inference based on a knowledge base constructed based on past experience and knowledge.
そこで、本発明はこのような問題点を解決するためにな
されたものであり常に高炉炉内のガス流及び装入物分布
状況を適確に判断し、最適な装入物分布制御を実施でき
るような高炉の操業方法を得る事を目的とする。Therefore, the present invention has been made in order to solve such a problem, and it is always possible to accurately judge the gas flow and the distribution state of the charging material in the blast furnace and perform the optimum charging material distribution control. The purpose is to obtain such a blast furnace operation method.
本発明に係る高炉の操業方法は上記課題を解決するため
になされたものであって、あらかじめ高炉炉内半径方向
のガス流や装入物の分布状況判断を行うための知識ベー
スを備えた知識工学システムにより、高炉炉内半径方向
のガス流や装入物の分布状況を推論し、該分布状況が適
正領域から外れていると判断された場合に、装入物分布
予測モデル計算を起動し、その時の装入原料条件、装入
物分布制御条件、操業条件等のオンラインデータにより
計算した炉内半径方向のガス流及び装入物分布特性の結
果をベース条件とし、該オンラインデータの中で装入物
分布制御条件のみを複数種類変更して計算した各分布特
性結果の中で、ベース条件に対する変化方向及び変化量
が、知識工学システムでの推論結果における現状の分布
状況を適正領域に戻すのに最も適する装入物分布制御条
件を選出し、該装入物分布制御条件に従って実炉アクシ
ョンを実行することを特徴とする高炉の装入物分布制御
方法である。The operation method of the blast furnace according to the present invention was made in order to solve the above-mentioned problems, and a knowledge provided with a knowledge base for judging the distribution state of the gas flow and the charge in the radial direction in the blast furnace in advance. The engineering system infers the gas flow in the radial direction in the blast furnace and the distribution of the charge, and if it is judged that the distribution is out of the proper range, the charge distribution prediction model calculation is started. , Based on the results of the gas flow and charge distribution characteristics in the radial direction in the furnace calculated from the online data of the charge material conditions, charge distribution control conditions, operating conditions, etc., in the online data Among the distribution characteristic results calculated by changing only multiple types of charge distribution control conditions, the direction of change and the amount of change with respect to the base condition should be set to the proper distribution state of the current distribution condition in the inference result in the knowledge engineering system. Elect a most suitable burden distribution control condition to be a burden distribution control method for a blast furnace, characterized in that to perform the actual furnace actions in 該装 burden distribution control condition.
〔作用〕 本発明においては、知識工学システムにより炉内状況の
推論を行う事により、炉内半径方向のガス流及び装入物
分布状況の変化を迅速かつ的確に捕らえ、種々の分布制
御方法による装入物分布特性変化をオンラインデータを
用いて装入物分布予測モデル計算により定量的に把握
し、計算結果の中から最適装入物分布制御方法を知識工
学システムの推論結果に基づいて選出し、実炉アクショ
ンとして採用する。[Operation] In the present invention, by inferring the in-reactor situation by the knowledge engineering system, changes in the gas flow and the charge distribution situation in the in-reactor radial direction are quickly and accurately captured, and various distribution control methods are used. Quantitative understanding of changes in the characteristics of the charge distribution by using online data to predict the charge distribution prediction model, and select the optimum charge distribution control method from the calculation results based on the inference results of the knowledge engineering system. , Adopted as an actual furnace action.
以下、本発明の実施例を図面に基づいて説明する。第１
図は本発明の一実施例に係る処理及びデータの流れの説
明図である。高炉１からの情報は、プロセスデータ処理
２により知識工学システム及び装入物分布予測モデル計
算で使用可能な状態とする。装入物分布予測モデルとし
ては、鐡と鋼、70(1984)，S47に示されているような、
炉頂部へ装入された原料の半径方向の堆積形状や粒度分
布、ガス流分布等を、装入条件やコークス崩れ現象等を
考慮して求めることができる数式モデルを用いる。該高
炉情報から、知識工学システムにより炉況判断３を行
い、炉内半径方向のガス流分布状況を把握する。図にお
いて、一点鎖線で囲まれた範囲は装入物分布予測モデル
計算を実行する部分であり、知識工学システムによる炉
況判断３の結果、装入物分布制御アクションが必要と判
定された時に起動する。該モデル計算の起動は知識工学
システムの判定結果に従い自動的に行うか、又は炉況判
断３を端末９に出力し、それに従って操業者１２が入力
端末１０の操作により行っても良い。装入物分布予測モ
デルの計算は初めにプロセスデータ、知識工学システム
からの炉況判断結果のデータ、操業者の設定データ等に
基づき計算用データ作成４を行う。計算用データは、オ
ンラインデータを用いた現在の装入物分布特性の予測計
算用のデータと装入物分布制御条件を変更した複数パタ
ーンの計算用データを含んだものであり、該複数パター
ンのデータにより装入物分布予測モデル計算５を行う。
該複数パターンのデータによる装入物分布予測モデル計
算結果の装入物分布形状表示や現在の分布特性から、装
入物分布制御条件変更後の分布特性の変化を示したデー
タの表示等を行うための計算結果後処理６を実行する。
計算結果データは出力端末１１に表示し、操業者１３が
出力端末１１に表示された装入物分布予測モデル計算結
果と、出力端末９に表示された知識工学システムによる
炉内半径方向分布状況判定結果に基づいて、最適装入物
分布制御条件を選出し、実行装入物分布制御８を行う。
該最適装入物分布制御条件の選出は、知識工学システム
による炉況判断３の結果のデータと装入物分布予測モデ
ル計算結果のデータを知識工学システムのデータベース
として取込み、装入物分布制御条件を選出するための知
識ベースによる推論によって実行してもよい。Embodiments of the present invention will be described below with reference to the drawings. First
The figure is an illustration of the flow of processing and data according to an embodiment of the present invention. The information from the blast furnace 1 is made available by the process data processing 2 in the knowledge engineering system and the charge distribution prediction model calculation. As a charge distribution prediction model, as shown in Teki and Steel, 70 (1984), S47,
A mathematical model is used that can determine the deposition shape, particle size distribution, gas flow distribution, etc. in the radial direction of the raw material charged to the furnace top, in consideration of charging conditions, coke collapse phenomenon, and the like. Based on the blast furnace information, the furnace condition judgment 3 is performed by the knowledge engineering system to grasp the gas flow distribution condition in the furnace radial direction. In the figure, the area surrounded by the one-dot chain line is the part that executes the charge distribution prediction model calculation, and is started when the charge distribution control action is determined to be necessary as a result of the reactor condition judgment 3 by the knowledge engineering system. To do. The activation of the model calculation may be automatically performed according to the determination result of the knowledge engineering system, or the reactor condition determination 3 may be output to the terminal 9 and the operator 12 may operate the input terminal 10 accordingly. In the calculation of the charge distribution prediction model, calculation data creation 4 is first performed based on the process data, the data of the reactor condition judgment result from the knowledge engineering system, the operator's setting data, and the like. The calculation data includes data for predictive calculation of current charge distribution characteristics using online data and calculation data of a plurality of patterns with changed charge distribution control conditions. The charge distribution prediction model calculation 5 is performed based on the data.
The charge distribution prediction model calculation result based on the data of the plurality of patterns is displayed, and the data showing the change of the distribution characteristics after the change of the charge distribution control conditions is displayed from the current distribution characteristics. The calculation result post-processing 6 is executed.
The calculation result data is displayed on the output terminal 11, and the operator 13 judges the distribution distribution model of the charge distribution displayed on the output terminal 11 and the in-reactor radial distribution status determination by the knowledge engineering system displayed on the output terminal 9. Based on the result, the optimum charge distribution control condition is selected and the execution charge distribution control 8 is performed.
The optimum charge distribution control condition is selected by taking in the data of the result of the furnace condition judgment 3 by the knowledge engineering system and the data of the calculation result of the charge distribution prediction model as a database of the knowledge engineering system to determine the charge distribution control condition. May be performed by inference based on a knowledge base for selecting.
個々の判断及び処理内容を図面に基づいてさらに詳しく
説明する。第２図は、知識工学システムにおける、高炉
の情報から炉内半径方向のガス流分布状況の判断に至る
までのフロー図である。ガス流及び装入物分布状況を判
断するための検出端として、装入物表面温度分布を測定
するサーモビュアー１５、炉頂部半径方向ガス温度分布
を測定する炉頂ゾンデ１６、炉周辺部のコークス及び鉱
石の層厚を測定する層厚計１７、シャフト上部高さでの
半径方向ガス温度及び成分分布を測定するシャフト上部
ゾンデ１８、炉体各部温度計１９、炉体各部圧力計２０
などがあり、これらの情報と、炉熱レベル、通気状況、
荷降下状況等の情報に基づき、知識工学システムによ
り、高炉操業状況の結合判定２１を行い、装入物分布制
御アクション必要性の判定２２及び半径方向ガス流分布
状況判定２３を行う。半径方向ガス流分布状況判定２３
において炉の半径方向を中心部、中間部、周辺部の３領
域に分け、ガス流割合を表現する三角ダイアグラムを用
い、現在のガス流分布状況と、目標値との偏差を捕え、
以降の最適装入物分布制御条件の選出に用いる。本発明
の実施例においては、現状のガス流分布割合は狙い値に
対し中心流が３％過多、周辺流が３％不足となってい
る。Each judgment and processing content will be described in more detail with reference to the drawings. FIG. 2 is a flow chart from the information of the blast furnace to the judgment of the gas flow distribution condition in the radial direction in the knowledge engineering system. As a detection end for determining the gas flow and the distribution state of the charged material, a thermoviewer 15 for measuring the surface temperature distribution of the charged material, a furnace top sonde 16 for measuring the gas temperature distribution in the furnace top radial direction, and a coke in the peripheral area of the furnace And a layer thickness gauge 17 for measuring the layer thickness of the ore, a shaft upper sonde 18 for measuring the radial direction gas temperature and component distribution at the shaft upper height, a furnace body thermometer 19, a furnace body pressure gauge 20
And so on, along with this information, furnace heat level, ventilation status,
Based on the information such as the load drop situation, the knowledge engineering system performs the joint determination 21 of the blast furnace operation situation, the determination 22 of the charge distribution control action necessity, and the determination 23 of the radial gas flow distribution situation. Radial gas flow distribution status judgment 23
In the furnace, the radial direction of the furnace is divided into three regions, the central part, the middle part, and the peripheral part, and a triangular diagram expressing the gas flow rate is used to capture the deviation between the current gas flow distribution state and the target value.
It is used for the selection of the optimum charge distribution control conditions thereafter. In the embodiment of the present invention, the current gas flow distribution ratio is 3% more in the central flow and 3% less in the peripheral flow than the target value.
次に、装入物分布予測モデル計算によるケース検討の例
を、第３図に基づいて説明する。装入物分布制御条件を
種々に変更したデータの作成において、本発明の実施例
では装入物分布制御手段２４として下記５項目を採用し
た。Next, an example of the case study by the calculation of the charge distribution prediction model will be described with reference to FIG. In creating data in which the charge distribution control conditions are variously changed, the following five items are adopted as the charge distribution control means 24 in the embodiment of the present invention.
ａ．炉内半径方向原料装入位置 ｂ．装入面レベル ｃ．コークス・鉱石ベース（１チャージの装入量） ｄ．焼結鉱細粒使用割合 ｅ．炉内への原料装入時の時系列排出粒度パターン これらの制御手段毎に、現状の制御条件を基準として装
入物分布制御条件変更処理２８を行う。ここで、現状の
制御条件はオンラインデータの装入物分布制御条件２５
を使用する。以下に装入物分布制御条件変更処理２８の
内容を説明する。a. Radial raw material charging position in the furnace b. Charging surface level c. Coke and ore base (charge amount of 1 charge) d. Sintered fine grain usage rate e. Time-series discharge particle size pattern at the time of charging the raw material into the furnace For each of these control means, the charging distribution control condition changing process 28 is performed based on the current control conditions. Here, the current control condition is the charge distribution control condition 25 of the online data.
To use. The contents of the charge distribution control condition changing process 28 will be described below.
ａ．炉内半径方向原料装入位置、変更 鉱石の装入を現状より１ノッチ中心方向へシフトする
（以降ａ＋と記す） 鉱石の装入を現状より１ノッチ周辺方向へシフトする
（以降ａ−と記す） ｂ．装入面レベル変更 現状より0.5ｍ上昇する（以降ｂ＋と記す） 現状より0.5ｍ低下する（以降ｂ−と記す） ｃ．コークス・鉱石ベース変更 鉱石ベースをチャージ当たり１ｔ増加、コークスベー
スは現状の鉱石とコークスの比を一定に保つ量だけ増加
する。（以降ｃ＋と記す） 鉱石ベースをチャージ当たり１ｔ減少、コークスベー
スは現状の鉱石とコークスの比を一定に保つ量だけ減少
する（以降ｃ−と記す） ｄ．焼結鉱細粒使用割合変更 現状より鉱石ベースに対する焼結鉱細粒割合を１％増
加する。（以降ｄ＋と記す） 現状より、鉱石ベースに対する焼結鉱細粒割合を１％
減少する。（以降ｄ−と記す） ｅ．炉内へのの原料装入時の時系列排出粒度パターン変
更 １ダンプ鉱石装入時の開始から終了までの時間を横軸
に取り、平均粒径を縦軸に取った平均粒径の経時変化を
直線近似した時のグラフの傾きを１％増加する。（以降
ｅ＋と記す） 上記グラフの傾きを１％減少する。（以降ｅ−と記
す） 該装入物分布制御条件変更処理２８により作成した現状
を含めた複数の装入物分布制御条件と、使用原料粒度条
件や送風条件等２６の装入物分布制御条件以外のオンラ
インデータと、設備条件等定数データ２７に基づいて計
算用データファイル２９を作成する。該計算データによ
り、装入物分布予測モデル計算３０を実行し、得られた
計算結果データファイル３１に基づき、画面表示や、現
状からの変化量の計算等の計算結果後処理３２を行う。a. Radial in-furnace raw material charging position, change Shifting the ore charging toward the center of 1 notch from the current state (hereinafter referred to as a +) Shifting the ore charging toward the 1 notch periphery from the current state (hereinafter referred to as a-) ) B. Change of charging surface level 0.5m higher than the current level (hereinafter referred to as b +) 0.5m lower than the current level (hereinafter referred to as b-) c. Change Coke / Ore Base Increase the ore base by 1 ton per charge, and increase the coke base by the amount that keeps the current ratio of ore and coke constant. (Hereinafter referred to as c +) The ore base is reduced by 1t per charge, and the coke base is reduced by an amount that keeps the current ratio of ore and coke constant (hereinafter referred to as c-). D. Change of the ratio of sinter fine particles used Increase the ratio of sinter fine particles to the ore base by 1% from the current state. (Hereinafter, referred to as d +) From the present situation, the ratio of sintered ore fine particles to the ore base is 1%.
Decrease. (Hereinafter referred to as d-) e. Change in time-series discharge particle size pattern when charging raw material into the furnace. 1 Time change from start to end of dump ore charging on the horizontal axis and average particle size on the vertical axis. The slope of the graph when linearly approximated is increased by 1%. (Hereinafter referred to as e +) The slope of the above graph is reduced by 1%. (Hereinafter referred to as e-) A plurality of charged material distribution control conditions including the current state created by the charged material distribution control condition change processing 28, and charged material distribution control conditions 26 such as raw material particle size conditions and blast conditions. A calculation data file 29 is created based on online data other than the above and constant data 27 such as equipment conditions. Based on the calculation data, the charge distribution prediction model calculation 30 is executed, and based on the obtained calculation result data file 31, the calculation result post-processing 32 such as screen display and calculation of the amount of change from the current state is performed.
第４図は、装入物分布予測モデル計算結果の出力例であ
り、(a)は炉内半径方向装入物堆積形状であり、３３は
コークス層、３４及び３５は鉱石層である。(b)は炉内
半径方向鉱石コークス比（ｏ／ｃ）分布、(c)は炉内半
径方向鉱石平均粒度分布である。これらの分布特性図に
より、現状と装入物分布制御条件変更後との分布特性の
違いを定量的に把握する。第５図は、装入物分布予測モ
デル計算結果の炉内半径方向ガス流分布割合を三角図に
示したものであり、ａ＋ａ−……ｅ−の記号は前記のそ
れぞれの装入物分布条件変更を行った場合の計算結果を
表わす。該三角図により装入物分布条件変更によるガス
流分布変化を容易に把握する事ができる。図の中で、点
線の円で囲まれた領域は、１回のアクションでのガス流
分布調整許容範囲であり、過去の実炉アクション実績に
おいて操業の変動を生じない最大のアクションによるガ
ス流分布割合の変化を現状を中心点として表わしたもの
である。従って分布制御条件変更のアクションは、ガス
流分布変化が該ガス流分布調整許容範囲内のものを採用
することが望ましい。FIG. 4 is an output example of the calculation result of the charge distribution prediction model, (a) is the radial charge deposit shape in the furnace, 33 is a coke layer, and 34 and 35 are ore layers. (b) is the radial ore coke ratio (o / c) distribution in the furnace, and (c) is the average particle size distribution of the ore in the furnace in the radial direction. Based on these distribution characteristic diagrams, the difference in distribution characteristics between the current state and the state after the change of the charge distribution control condition is quantitatively grasped. FIG. 5 is a triangular diagram showing the distribution ratio of gas flow in the reactor in the radial direction as a result of the calculation of the charge distribution prediction model. The symbols a + a -... e- are the charge distribution conditions for each of the above. Shows the calculation results when changes are made. The triangular diagram makes it possible to easily grasp the change in the gas flow distribution due to the change in the charge distribution condition. In the figure, the area enclosed by the dotted circle is the gas flow distribution adjustment permissible range for one action, and the gas flow distribution by the maximum action that does not cause fluctuations in operation in the past actual reactor action results. It shows the change in the ratio with the current situation as the central point. Therefore, as the action of changing the distribution control condition, it is desirable to adopt an action in which the change in the gas flow distribution is within the allowable range for adjusting the gas flow distribution.
これらの計算結果の中で、ａ＋の条件が現状に対し中心
ガス流割合が３％減少し、周辺ガス流割合が３％増加す
る方向にあり、第２図の知識工学システムによる半径方
向ガス流分布状況２３の判定結果における狙い値からの
現状のズレを矯正するのに最も適したアクションである
と判定できる。この判定は、第１図に示すように操業者
１３が行っても良いし、最適装入物分布制御条件選出７
を行うための知識ベースを備えた知識工学システムで行
っても良い。In these calculation results, the condition of a + tends to decrease the central gas flow ratio by 3% and increase the peripheral gas flow ratio by 3% compared to the current condition. It can be determined that the action is most suitable for correcting the current deviation from the target value in the determination result of the distribution status 23. This determination may be made by the operator 13 as shown in FIG. 1, or the optimum charge distribution control condition selection 7
It may be performed by a knowledge engineering system having a knowledge base for performing.
以上の結果より、実炉における装入物分布制御条件とし
てａ＋の鉱石の装入を現状より１ノッチ中心方向へシフ
トを採用する。From the above results, as the charge distribution control condition in the actual furnace, the a + ore charge is shifted toward the center of one notch from the current condition.
本発明は以上のように、知識工学システムにより炉内半
径方向分布状況を判断し、その時のオンラインデータに
基づいて装入物分布予測モデル計算を複数条件行い、こ
れらの結果から最適装入物分布制御条件を選出すること
により、的確かつ迅速な実炉分布調整アクションが実行
できる。As described above, the present invention determines the distribution state in the radial direction in the reactor by the knowledge engineering system, performs multiple conditions of the charge distribution prediction model calculation based on the online data at that time, and optimizes the charge distribution from these results. By selecting the control conditions, it is possible to execute an accurate and quick action for adjusting the actual reactor distribution.
第１図は、本発明の処理およびデータの流れの説明図、 第２図は、本発明の知識工学システムにおける高炉の情
報から炉内半径方向のガス流分布状況の判断に至るまで
のフロー図、 第３図は、本発明の装入物分布予測モデル計算による複
数条件の計算のフロー図、 第４図は、本発明の装入物分布予測モデル計算結果の出
力例の説明図、 第５図は、本発明の装入物分布予測モデル計算結果の炉
内半径方向ガス流分布割合をプロットした三角図であ
る。FIG. 1 is an explanatory view of the processing and data flow of the present invention, and FIG. 2 is a flow chart from the information of the blast furnace in the knowledge engineering system of the present invention to the judgment of the gas flow distribution condition in the radial direction in the furnace. FIG. 3 is a flow chart of calculation of a plurality of conditions by the charge distribution prediction model calculation of the present invention. FIG. 4 is an explanatory diagram of an output example of the charge distribution prediction model calculation result of the present invention. The figure is a triangular diagram in which the ratio of gas flow distribution in the radial direction in the furnace as a result of calculation of the charge distribution prediction model of the present invention is plotted.
───────────────────────────────────────────────────── フロントページの続き (72)発明者 織田 博史 千葉県君津市君津１番地 新日本製鐵株式 会社君津製鐵所内 (72)発明者 渡辺 敏 千葉県君津市君津１番地 新日本製鐵株式 会社君津製鐵所内 (72)発明者 平 政道 千葉県君津市君津１番地 新日本製鐵株式 会社君津製鐵所内 ─────────────────────────────────────────────────── ─── Continuation of front page (72) Inventor Hiroshi Oda 1 Kimitsu, Kimitsu-shi, Chiba Nippon Steel Corporation Stock (72) Inventor, Satoshi Watanabe 1 Kimitsu, Chiba Shin-Nihon Steel Co., Ltd. Company Kimitsu Works (72) Inventor Hira Masamichi Kimitsu City Chiba Prefecture Kimitsu 1 Shin Nippon Steel Co., Ltd. Kimitsu Works Ltd.
Claims (1)
入物の分布状況判断を行うための知識ベースを備えた知
識工学システムにより、高炉炉内半径方向のガス流や装
入物の分布状況を推論し、該分布状況が適正領域から外
れていると判断された場合に、装入物分布予測モデル計
算を起動し、その時の装入原料条件、装入物分布制御条
件、操業条件等のオンラインデータにより計算した炉内
半径方向のガス流及び装入物分布特性の結果をベース条
件とし、該オンラインデータの中で装入物分布制御条件
のみを複数種類変更して計算した各分布特性結果の中
で、ベース条件に対する変化方向及び変化量が、知識工
学システムでの推論結果における現状の分布状況を適正
領域に戻すのに最も適する装入物分布制御条件を選出
し、該装入物分布制御条件に従って実炉アクションを実
行することを特徴とする高炉の装入物分布制御方法。1. A distribution of gas flow and charge in the radial direction of the blast furnace by a knowledge engineering system equipped with a knowledge base for judging the distribution status of the gas flow and charge of the blast furnace in the radial direction in advance. When the situation is inferred and it is determined that the distribution situation is out of the proper range, the charge distribution prediction model calculation is started, and the charge material condition, charge distribution control condition, operation condition, etc. at that time are started. Based on the results of the gas flow in the furnace radial direction and the distribution characteristics of the charge calculated from the online data of the above, the distribution characteristics calculated by changing only a plurality of kinds of the charge distribution control conditions in the online data Among the results, the charge distribution control condition is selected which is the most suitable for the change direction and the change amount with respect to the base condition to return the current distribution condition in the inference result in the knowledge engineering system to the proper region. Distribution control Burden distribution control method for a blast furnace, characterized in that to perform the actual furnace actions in the matter.
Priority Applications (10)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP88689A JPH0663009B2 (en) | 1989-01-06 | 1989-01-06 | Blast furnace charge distribution control method |
| EP93100520A EP0542717B1 (en) | 1988-12-20 | 1989-12-14 | Blast furnace operation management method and apparatus |
| ES94117502T ES2157233T3 (en) | 1988-12-20 | 1989-12-14 | METHOD AND APPARATUS FOR THE MANAGEMENT OF THE OPERATION OF A HIGH OVEN. |
| ES93100520T ES2097936T3 (en) | 1988-12-20 | 1989-12-14 | METHOD AND APPARATUS FOR CONDUCTING THE OPERATION OF A HIGH OVEN. |
| US07/450,390 US4976780A (en) | 1988-12-20 | 1989-12-14 | Blast furnace operation management method and apparatus |
| EP89313087A EP0375282B1 (en) | 1988-12-20 | 1989-12-14 | Blast furnace operation management method and apparatus |
| EP94117502A EP0641863B1 (en) | 1988-12-20 | 1989-12-14 | Blast furnace operation management method and apparatus |
| ES89313087T ES2085285T3 (en) | 1988-12-20 | 1989-12-14 | METHOD AND APPARATUS FOR THE MANAGEMENT OF THE OPERATION OF A HIGH OVEN. |
| AU46884/89A AU612531B2 (en) | 1988-12-20 | 1989-12-18 | Blast furnace operation management method and apparatus |
| CN89109414.8A CN1021833C (en) | 1988-12-20 | 1989-12-20 | Blast furnace operation management method and apparatus |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP88689A JPH0663009B2 (en) | 1989-01-06 | 1989-01-06 | Blast furnace charge distribution control method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JPH02182815A JPH02182815A (en) | 1990-07-17 |
| JPH0663009B2 true JPH0663009B2 (en) | 1994-08-17 |
Family
ID=11486158
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP88689A Expired - Fee Related JPH0663009B2 (en) | 1988-12-20 | 1989-01-06 | Blast furnace charge distribution control method |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JPH0663009B2 (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2020535566A (en) * | 2017-09-19 | 2020-12-03 | コベストロ・エルエルシー | Technology for custom designing products |
-
1989
- 1989-01-06 JP JP88689A patent/JPH0663009B2/en not_active Expired - Fee Related
Also Published As
| Publication number | Publication date |
|---|---|
| JPH02182815A (en) | 1990-07-17 |
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