JP7735985B2 - Method for predicting sinter quality and method for producing sinter using the same - Google Patents
Method for predicting sinter quality and method for producing sinter using the sameInfo
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Description
本発明は、高炉の原料として用いられる焼結鉱の焼結鉱品質の予測方法および当該予測方法を用いた焼結鉱の製造方法に関する。 The present invention relates to a method for predicting the quality of sintered ore used as a raw material for blast furnaces, and a method for producing sintered ore using this prediction method.
高炉主原料の大部分を占める焼結鉱は、例えば焼結体として幅約５ｍ、厚さ約６００ｍｍの大焼結鉱（以降、焼結ケーキと称す）が連続的に焼成され、破砕およびスクリーンの過程を経て、粒径５ｍｍ以上の焼結鉱（以降、成品焼結鉱と称す）として高炉に送られる。ここで、焼結ケーキに対する成品焼結鉱の重量割合（以降、焼結鉱歩留と称す）の向上による、製造コストの削減およびＣＯ２排出量の削減が重要な課題である。従って、歩留の向上には、－５ｍｍ（粒径５ｍｍ未満）の細粒の発生を抑制する必要がある。細粒は焼結ケーキの破砕時や成品焼結鉱の搬送時に生じることが推定されるため、焼結鉱歩留は、焼結鉱の強度が支配的と推定される。 Sintered ore, which accounts for the majority of the main raw material in a blast furnace, is continuously fired as a sintered body, for example, in large sintered ore pieces approximately 5 m wide and 600 mm thick (hereinafter referred to as sinter cake). After being crushed and screened, the resulting sintered ore with a particle size of 5 mm or more (hereinafter referred to as product sintered ore) is sent to the blast furnace. Here, reducing production costs and CO2 emissions by increasing the weight ratio of product sintered ore to the sintered ore cake (hereinafter referred to as sinter yield) is an important issue. Therefore, to improve yield, it is necessary to suppress the generation of fine particles with a particle size of -5 mm (less than 5 mm). Since fine particles are presumably generated during the crushing of the sintered cake and the transportation of the product sintered ore, the strength of the sintered ore is presumably the dominant factor in determining sintered ore yield.
非特許文献１によると、焼結鉱強度の向上には、液相成分（例えば、カルシウムフェライト）を増加させることが有効である。焼結鉱は液相結合により強度を確保していることからも分かるように、焼結鉱強度の向上には、焼結鉱中の液相割合（以降、溶融率と称す）を上昇させることが重要であることが分かる。 According to Non-Patent Document 1, increasing the liquid phase component (e.g., calcium ferrite) is effective in improving the strength of sintered ore. Since the strength of sintered ore is ensured by liquid phase bonding, it is clear that increasing the liquid phase ratio in sintered ore (hereinafter referred to as the melting rate) is important in improving the strength of sintered ore.
しかしながら、焼結鉱の溶融率はオフラインで製造後の焼結鉱を採取し、断面観察やＸＲＤ等で評価する必要があるので、オンラインでの制御には使用することができない課題がある。以上より、焼結鉱溶融率のオンライン予測が必要である。焼結鉱の溶融率は、焼結層内温度および原料成分に依存する。温度は原料条件および操業条件によって左右される。成分は、例えばＦｅ２Ｏ３－ＣａＯ二元系状態図からも分かるように、ＣａＯの濃度によって融点が大きく変化する。焼結鉱にはその他に、ＳｉＯ２、Ａｌ２Ｏ３、ＭｇＯ等が含まれる多成分系だが、これら焼結鉱の成分は、各鉄鉱石原料の配合計算によって予測することができる。 However, the melting rate of sintered ore must be evaluated offline by sampling the sintered ore after production and using cross-sectional observation or XRD, which means that it cannot be used for online control. For these reasons, online prediction of the melting rate of sintered ore is necessary. The melting rate of sintered ore depends on the temperature in the sintering bed and the raw material composition. The temperature is influenced by the raw material conditions and operating conditions. As can be seen from the Fe 2 O 3 -CaO binary phase diagram, for example, the melting point varies greatly depending on the CaO concentration. Sintered ore is a multi-component system that also contains SiO 2 , Al 2 O 3 , MgO, etc., but the composition of these sintered ore components can be predicted by calculating the blending ratio of each iron ore raw material.
一方、焼結鉱製造時における焼結原料の装入層の焼結温度履歴を測定する方法として、例えば、特許文献１には、熱電対で実測した高さ方向の温度データから特徴量を計算することで操業状態を管理する手法が開示されている。しかしながら、温度が測定できても、温度増減の根本的な原因が分からないがために、理論的アプローチによる操業改善にはつながらない点が課題である。 Meanwhile, as a method for measuring the sintering temperature history of the sintering raw material charging layer during sinter production, for example, Patent Document 1 discloses a technique for managing operational status by calculating feature values from temperature data in the height direction measured using thermocouples. However, even if the temperature can be measured, the fundamental causes of temperature increases and decreases are unknown, which means that this method does not lead to operational improvements through a theoretical approach, which is an issue.
焼結温度履歴を理論的に推定する方法は、すでに非特許文献２で伝熱モデルが数式化されており、例えば、特許文献２には非特許文献３の伝熱モデルを用いて、燃焼性の異なる炭材使用時にも比較的高精度に温度履歴を計算できる方法が開示されている。本手法では、温度を制御するための因子を物理的なパラメーターとして抽出することができる。しかしながら、伝熱モデルによる計算温度から溶融率を推定する手法が不足しているため、オンラインで焼結鉱歩留を制御することができない課題があった。 A method for theoretically estimating sintering temperature history has already been formulated using a heat transfer model in Non-Patent Document 2. For example, Patent Document 2 discloses a method that uses the heat transfer model of Non-Patent Document 3 to calculate temperature history with relatively high accuracy even when using carbonaceous materials with different combustibility. This method makes it possible to extract factors for controlling temperature as physical parameters. However, there is a lack of a method for estimating the melting rate from the temperature calculated using a heat transfer model, which has led to the issue of not being able to control sinter yield online.
前述の通り、歩留は溶融率に依存することが考えられるが、焼結鉱の溶融率を推定するには、オフラインで製造後の焼結鉱を採取し、断面観察やＸＲＤ等で評価する必要がある。そのため、焼結鉱の歩留に影響を及ぼす溶融率をオンラインで管理できず、焼結鉱歩留を予測することが難しいといった課題があった。 As mentioned above, it is thought that yield depends on the melting rate, but to estimate the melting rate of sintered ore, it is necessary to sample sintered ore offline after production and evaluate it using cross-sectional observation, XRD, etc. As a result, the melting rate, which affects sintered ore yield, cannot be managed online, making it difficult to predict sintered ore yield, which has been an issue.
本発明は、このような事情に鑑みてなされたものであって、その目的とするところは、、焼結鉱溶融率をオンラインで把握し、歩留を管理できる焼結鉱品質の予測方法およびそれを用いた焼結鉱の製造方法を提案することにある。 The present invention was made in light of these circumstances, and its purpose is to propose a method for predicting sinter ore quality that can grasp the sinter ore melting rate online and manage yield, as well as a method for manufacturing sinter ore using the same.
本発明は、ドワイトロイド式の焼結機の無端移動式のパレット台車に焼結原料を装入して装入層を形成させ、前記装入層を焼結して製造される焼結鉱の焼結鉱品質の予測方法であって、焼結鉱の製造条件と伝熱モデルとを用いて前記装入層内の焼結温度履歴を算出し、算出した前記焼結温度履歴と化学成分を用いて前記焼結鉱の溶融率を予測し、前記予測した焼結鉱の溶融率から歩留を予測することを特徴とする、焼結鉱品質の予測方法である。 The present invention is a method for predicting the quality of sintered ore produced by charging sinter raw materials onto the endless moving pallet cart of a Dwight Lloyd sintering machine to form a charging bed and sintering the charging bed. This method calculates the sintering temperature history within the charging bed using sintered ore production conditions and a heat transfer model, predicts the melting rate of the sintered ore using the calculated sintering temperature history and chemical components, and predicts the yield from the predicted melting rate of the sintered ore.
なお、前記のように構成される本発明に係る焼結鉱品質の予測方法においては、
（１）前記焼結鉱の製造条件として、前記焼結原料に配合される原料の成分濃度、粒度および配合量と、前記パレット台車の速度と、前記装入層の層厚と、負圧と、を用いること、
（２）前記焼結鉱の製造条件として、さらに、気体燃料吹込み量、酸素吹込み量および循環排ガス量のいずれか一つ以上を用いること、
（３）前記焼結鉱溶融率の予測を、予め求められる焼結温度履歴と焼結鉱成分との対応関係を用いて前記算出した焼結温度履歴に基づき行うこと、
がより好ましい解決手段となるものと考えられる。
In the method for predicting sinter quality according to the present invention configured as described above,
(1) The sintered ore production conditions include the component concentration, particle size, and blending amount of the raw material blended in the sintered raw material, the speed of the pallet cart, the layer thickness of the charging layer, and the negative pressure.
(2) The sintered ore production conditions further include one or more of a gaseous fuel injection amount, an oxygen injection amount, and a circulating exhaust gas amount.
(3) The prediction of the sintered ore melting rate is carried out based on the calculated sintering temperature history using a correspondence relationship between a sintered ore component and a sintered ore temperature history obtained in advance;
This is considered to be a more preferable solution.
また、本発明は、上述した焼結鉱品質の予測方法を用いる焼結鉱の製造方法であって、前記焼結鉱品質の予測方法を用いて予測した歩留から、予め定められた焼結鉱の歩留になる焼結鉱の製造条件を求め、求められた前記製造条件で前記焼結鉱を製造することを特徴とする、焼結鉱の製造方法である。 The present invention also provides a method for producing sintered ore using the above-described method for predicting sintered ore quality, which involves determining sintered ore production conditions that result in a predetermined sintered ore yield from the yield predicted using the sintered ore quality prediction method, and producing the sintered ore under the determined production conditions.
本発明に係る焼結鉱品質の予測方法の実施により、短時間で焼結鉱溶融率が予測できるので、焼結鉱溶融率をオンラインで把握し、歩留を管理できるようになる。さらに、予測された焼結鉱溶融率が目標とする焼結鉱溶融率になるように焼結鉱の製造条件を設定することで、焼結鉱の溶融率・歩留を制御でき、高品質な焼結鉱の製造が実現できる。 By implementing the sinter ore quality prediction method of the present invention, the sinter ore melting rate can be predicted in a short time, allowing the sinter ore melting rate to be monitored online and yield to be managed. Furthermore, by setting the sinter ore production conditions so that the predicted sinter ore melting rate matches the target sinter ore melting rate, the sinter ore melting rate and yield can be controlled, enabling the production of high-quality sinter ore.
以下、本発明の実施の形態について具体的に説明する。なお、以下の実施形態は、本発明の技術的思想を具体化するための装置や方法を例示するものであり、構成を下記のものに特定するものでない。すなわち、本発明の技術的思想は、特許請求の範囲に記載された技術的範囲内において、種々の変更を加えることができる。 The following describes in detail the embodiments of the present invention. Note that the following embodiments are intended to exemplify devices and methods that embody the technical concepts of the present invention, and are not intended to limit the configuration to those described below. In other words, the technical concepts of the present invention can be modified in various ways within the technical scope set forth in the claims.
＜本発明の実施対象となる焼結鉱の製造設備について＞
図１は、本実施形態に係る焼結品質の予測方法が実施できる焼結鉱の製造設備１の一例を示す模式図である。焼結鉱の製造設備１は、造粒装置であるドラムミキサー２と、焼結機３と、破砕機４と、クーラー５と、篩分装置６とを有する。鉄含有原料、副原料および炭材やコークス粉といった凝結材を含む焼結原料は、造粒水が添加されてドラムミキサー２で造粒される。造粒された焼結原料は焼結機３に搬送される。
<Sintered ore manufacturing equipment to which the present invention is applied>
1 is a schematic diagram showing an example of a sinter ore production facility 1 in which the sinter quality prediction method according to this embodiment can be implemented. The sinter ore production facility 1 includes a drum mixer 2, which is a granulating device, a sinter machine 3, a crusher 4, a cooler 5, and a sieving device 6. Sinter raw materials including iron-containing raw materials, auxiliary raw materials, and coagulating agents such as carbonaceous material and coke powder are granulated in the drum mixer 2 after granulation water is added. The granulated sinter raw materials are transported to the sinter machine 3.
焼結機３は、例えば、ドワイトロイド式の焼結機である。焼結機３は、焼結原料供給装置１１と、無端移動式のパレット台車１２と、点火炉１３と、ウインドボックス１４とを有する。造粒された焼結原料は、焼結原料供給装置１１からパレット台車１２に装入され、焼結原料の装入層が形成される。点火炉１３で装入層表層に含まれる凝結材が点火されるとともに、ウインドボックス１４を通じて装入層内の空気が下方へ吸引されることで、装入層内の燃焼溶融帯が装入層の下方に移動される。この燃焼溶融帯の移動により、装入層が焼結されて焼結ケーキとなる。 The sintering machine 3 is, for example, a Dwight Lloyd type sintering machine. The sintering machine 3 has a sintering material supply device 11, an endless moving pallet cart 12, an ignition furnace 13, and a wind box 14. Granulated sintering material is loaded from the sintering material supply device 11 onto the pallet cart 12, forming a sintering material charging layer. The ignition furnace 13 ignites the coagulant contained in the surface layer of the sintering material charging layer, and air within the sintering material charging layer is sucked downward through the wind box 14, moving the combustion and melting zone within the sintering material charging layer below the sintering material charging layer. This movement of the combustion and melting zone sinters the sintering material charging layer into a sintered cake.
ウインドボックス１４を通じて装入層内の空気を下方へ吸引する際、装入層の上方から気体燃料および／または酸素を富化した酸素富化空気を供給してもよい。気体燃料は、高炉ガス、コークス炉ガス、転炉ガス、都市ガス、天然ガス、メタンガス、エタンガス、プロパンガスおよびこれらの混合ガスから選ばれるいずれかの可燃性ガスである。 When air in the sintering bed is sucked downward through the wind box 14, gaseous fuel and/or oxygen-enriched air may be supplied from above the sintering bed. The gaseous fuel is any combustible gas selected from blast furnace gas, coke oven gas, converter gas, city gas, natural gas, methane gas, ethane gas, propane gas, and mixtures thereof.
焼結ケーキは破砕機４によって破砕され、クーラー５で冷却される。焼結ケーキの破砕物は、篩分装置６で粒径５ｍｍ以上の焼結鉱と粒径５ｍｍ未満の返鉱とに篩分けされる。返鉱は、再び、焼結原料に用いられる。このようにして焼結鉱は生産される。 The sinter cake is crushed by crusher 4 and cooled in cooler 5. The crushed sinter cake is sieved in sieving device 6 into sinter ore with a particle size of 5 mm or more and return ore with a particle size of less than 5 mm. The return ore is reused as sinter raw material. In this way, sinter ore is produced.
＜本発明の焼結鉱品質の予測方法について＞
本実施形態に係る焼結鉱品質の予測方法では、焼結鉱の製造設備１で製造される焼結鉱の焼結鉱溶融率を予測する。焼結鉱溶融率の予測は、まず、（１）焼結鉱の製造条件と伝熱モデルとを用いて焼結温度履歴を算出し、次いで、（２）焼結鉱の成分を原料の配合比から計算し、最後に、（３）前述の成分および算出した焼結温度履歴を用いて焼結鉱溶融率を予測する。好適な実施形態においては、焼結鉱溶融率の予測を、予め求められた焼結温度履歴と焼結鉱溶融率との対応関係を用いて算出した焼結温度履歴に基づき行う。その後、予測した焼結鉱の溶融率から歩留を予測する。
<Method for predicting sinter quality according to the present invention>
In the method for predicting sinter ore quality according to this embodiment, the sinter ore melting rate of sintered ore produced in sinter ore production equipment 1 is predicted. The sinter ore melting rate is predicted by first (1) calculating the sintering temperature history using the sinter ore production conditions and a heat transfer model, then (2) calculating the sinter ore components from the raw material blending ratio, and finally (3) predicting the sinter ore melting rate using the aforementioned components and the calculated sintering temperature history. In a preferred embodiment, the sinter ore melting rate is predicted based on the sintering temperature history calculated using a correspondence relationship between the sintering temperature history and the sinter ore melting rate, which is previously determined. The yield is then predicted from the predicted sinter ore melting rate.
＜（１）焼結温度履歴の算出について＞
焼結温度履歴の算出は、公知の手法である非特許文献２に記載の方法を用いて行う。具体的には、焼結原料に配合される鉄含有原料、副原料および凝結材の成分濃度、粒度および配合量と、パレット台車速度と、装入層の層厚と、負圧とを含む焼結鉱の製造条件と、伝熱モデルとを用いて焼結温度履歴を算出する。本実施形態において、伝熱モデルは、例えば、エネルギー保存式から導かれる固相の熱収支式（下記（１）式）および気相の熱収支式（下記（２）式）である。
<(1) Calculation of sintering temperature history>
The sintering temperature history is calculated using a known method described in Non-Patent Document 2. Specifically, the sintering temperature history is calculated using the component concentrations, particle sizes, and blending amounts of the iron-containing raw materials, auxiliary raw materials, and coagulant blended in the sintering raw materials, sinter production conditions including the pallet cart speed, the layer thickness of the charging layer, and the negative pressure, and a heat transfer model. In this embodiment, the heat transfer model is, for example, a solid phase heat balance equation (Equation (1) below) and a gas phase heat balance equation (Equation (2) below) derived from the energy conservation equation.
上記（１）、（２）式において、ρｓは固体の密度［ｋｇ／ｍ３］であり、Ｃｐ・ｓは固体の比熱［Ｊ／（ｋｇ×Ｋ）］であり、Ｔｓは固体の温度［Ｋ］であり、ｔは時間［ｓｅｃ］であり、ｄは平均粒径［ｍ］であり、εａは空隙率［－］であり、ｈは対流伝熱係数［Ｊ／（ｍ２×ｓ×Ｋ）］であり、Ｔｇはガス温度［Ｋ］であり、ｋｓは固体熱伝導度［Ｊ／（ｍ２×ｓ×Ｋ）］であり、Ｚは座標［ｍ］である。また、Ｑは焼結原料に含まれる各物質の反応熱［Ｊ／ｓ］であり、当該反応熱は、各物質の反応熱と反応速度とを乗じて算出する。上記（２）式において、ρｇはガスの密度［ｋｇ／ｍ３］であり、Ｃｐ・ｇはガスの比熱［Ｊ／（ｋｇ×Ｋ）］であり、ｕはガス流速［ｍ／ｓ］であり、Ｔは温度［Ｋ］であり、ｋｇはガス熱伝導度［Ｊ／（ｍ２×ｓ×Ｋ）］である。 In the above formulas (1) and (2), ρs is the density of the solid [kg/ m3 ], Cps is the specific heat of the solid [J/(kg×K)], Ts is the temperature of the solid [K], t is time [sec], d is the average particle size [m], εa is the porosity [-], h is the convective heat transfer coefficient [J/( m2 ×s×K)], Tg is the gas temperature [K], ks is the solid thermal conductivity [J/( m2 ×s×K)], and Z is the coordinate [m]. Also, Q is the reaction heat [J/s] of each substance contained in the sintering raw material, and the reaction heat is calculated by multiplying the reaction heat of each substance by the reaction rate. In the above equation (2), ρg is the gas density [kg/ m3 ], Cp ·g is the gas specific heat [J/(kg×K)], u is the gas flow rate [m/s], T is the temperature [K], and kg is the gas thermal conductivity [J/( m2 ×s×K)].
固体の密度ρｓおよび気体の密度ρｇは仮値を用いる。固体の密度ρｓの仮値として下記に記載の値を用い、気体の密度度ρｇの仮値として下記に記載の値を用いる。また、固体の比熱Ｃｐ・ｓおよびガスの比熱Ｃｐ・ｇは、それぞれ下記に記載の値を用いる。 Provisional values are used for the density ρs of a solid and the density ρg of a gas. The values listed below are used as provisional values for the density ρs of a solid, and the values listed below are used as provisional values for the density ρg of a gas. The values listed below are also used for the specific heats Cp s of a solid and Cp g of a gas, respectively.
＜固体の物性（ヘマタイトを使用）＞
＜ガスの物性（空気を使用）＞
以下、各物性について説明する。
固体の温度Ｔｓは、現在の固体の計算温度であり、また、ガスの温度Ｔｇは、現在のガスの計算温度である。時間ｔは、当該モデルを用いてどのくらいの時間間隔の温度変化を算出するかにより定められる設定値である。平均粒径ｄは造粒された焼結原料の平均粒径の実測値を用いる。空隙率εａは仮値を用いる。空隙率εａの仮値として「０．５」を用いる。対流伝熱係数ｈは、負圧と空隙率と平均粒径から風量を計算し、当該風量とランツ・マーシャルの式とを用いて算出できる。固体熱伝導度ｋｓは上記に記載の値を用いる。反応熱Ｑは、焼結原料に配合される成分濃度、粒度および配合量と、各成分の反応熱と、反応速度と、を用いて算出できる。ガス流速ｕは、負圧と空隙率と平均粒径とを用いて算出できる。負圧は、風箱に設けられる圧力計の実測値を用いる。ガスの熱伝導度ｋｇは、上記に記載の値を用いる。
Each physical property will be explained below.
The solid temperature Ts is the calculated temperature of the solid at present, and the gas temperature Tg is the calculated temperature of the gas at present. The time t is a set value determined by the time interval over which the temperature change is calculated using the model. The average particle size d is the measured value of the average particle size of the granulated sintering raw material. The porosity εa is a hypothetical value. 0.5 is used as the hypothetical value for the porosity εa . The convective heat transfer coefficient h can be calculated by calculating the air volume from the negative pressure, porosity, and average particle size, and then using this air volume and the Lanz-Marshall equation. The solid thermal conductivity ks uses the value described above. The reaction heat Q can be calculated using the concentration, particle size, and amount of the components mixed in the sintering raw material, the reaction heat of each component, and the reaction rate. The gas flow velocity u can be calculated using the negative pressure, porosity, and average particle size. The negative pressure is the measured value of the pressure gauge installed in the wind box. The gas thermal conductivity kg uses the value described above.
パレット台車の速度は、焼結鉱の製造条件として予め設定されるものであり、点火時間（高温にさらされる時間）や、計算開始から計算完了までの時間を定めるのに用いる。層厚も焼結鉱の製造条件として予め設定されるものであり、計算開始や計算終了までの時間を定めるのに用いる。 The speed of the pallet cart is preset as a sinter ore production condition and is used to determine the ignition time (time exposed to high temperatures) and the time from the start of calculation to completion. The layer thickness is also preset as a sinter ore production condition and is used to determine the time from the start of calculation to the end of calculation.
また、気体燃料吹込み装置や酸素ガス吹込み装置を有する焼結機を用いる場合、操業条件として、気体燃料の吹込み量、酸素ガスの吹込み量および循環排ガス量の1つ以上の操業条件を用いて（１）式の反応熱Ｑを修正してもよい。 Furthermore, when using a sintering machine equipped with a gaseous fuel injection device or an oxygen gas injection device, the reaction heat Q in equation (1) may be corrected using one or more of the operating conditions: the amount of gaseous fuel injected, the amount of oxygen gas injected, and the amount of circulating exhaust gas.
上記（１）式および（２）式に上記値と、ＴｓおよびＴｇに現在の温度を入力すると、設定した時間刻み（Δｔ：例えば１秒）後の温度変化が算出される。ＴｓおよびＴｇの初期温度は点火炉の温度である１３００℃を用いる。また、例えば、時間刻みが1秒で計算時間が３０分ならば、１８００個の温度データが取得され、当該温度データを用いて図２に示すような焼結温度履歴を示すグラフを作成できる。 By inputting the above values into the above formulas (1) and (2) and the current temperatures into Ts and Tg , the temperature change after a set time interval (Δt: for example, 1 second) is calculated. The initial temperature of Ts and Tg is 1300°C, which is the temperature of the ignition furnace. Furthermore, for example, if the time interval is 1 second and the calculation time is 30 minutes, 1800 pieces of temperature data are obtained, and a graph showing the sintering temperature history, as shown in Figure 2, can be created using the temperature data.
＜（２）焼結鉱溶融率の予測について＞
以下に説明するように、算出した焼結温度履歴を用いて、焼結鉱溶融率を予測する。まず、（１）式、（２）式および操業データを用いて装入層の焼結温度履歴を求める。焼結プロセスは下層吸引式のため、必然的に下層の温度が高くなる傾向がある。また、一般的に上層の温度が高いほど下層の温度も上昇するため、今回は焼結機高さ方向で最も高い温度（Ｔｍａｘ）を抽出した。
<(2) Prediction of sinter melting rate>
As explained below, the calculated sintering temperature history is used to predict the sinter ore melting rate. First, the sintering temperature history of the charging layer is calculated using equations (1) and (2) and operational data. Because the sintering process uses a lower layer suction method, the temperature of the lower layer inevitably tends to be higher. In addition, since the temperature of the upper layer generally increases as the temperature of the lower layer increases, the highest temperature (Tmax) in the height direction of the sinter machine was extracted in this study.
溶融率の算出には、ＸＲＤや断面観察など種々の方法が考えられるが、理論に基づいた状態図による計算を採用した。多成分系の計算ツールとして、Ｆａｃｔｓｔａｇｅ（登録商標）を使用した。しかし、計算には時間がかかるため、事前に複数の条件で計算して、重回帰を構築しておき、下記の式により簡易的に重回帰でオンライン計算する手法を用いた。図３に、(５)式の溶融率とＦａｃｔｓｔａｇｅ（登録商標）を用いて計算した溶融率との関係を示す。非常に良い相関が確認され、本手法で溶融率の予測に問題が無いことを確認した。 While various methods, such as XRD and cross-sectional observation, can be used to calculate the melting ratio, we adopted a theoretically based calculation using a phase diagram. Factstage (registered trademark) was used as a calculation tool for multi-component systems. However, as calculations take time, calculations were performed under multiple conditions in advance to construct a multiple regression, and a simple online calculation using multiple regression was then performed using the formula below. Figure 3 shows the relationship between the melting ratio in equation (5) and the melting ratio calculated using Factstage (registered trademark). An extremely good correlation was confirmed, confirming that there are no problems with predicting the melting ratio using this method.
図４（ａ）、（ｂ）に、実機焼結機の歩留と最高温度（比較例）および溶融率（実施例との関係を示す。温度単体での整理と比較して、溶融率にすることで、歩留と良い対応関係が得られた。本関係より、現状の溶融率を計算し、オンラインで歩留の予測が可能となる。また、歩留に目標値を設定することで、目指すべき溶融率が計算できる。次に、溶融率を制御するために操業条件を変更した。 Figures 4(a) and (b) show the relationship between the yield of an actual sintering machine and the maximum temperature (comparison example) and the melting rate (example). Compared to organizing the temperature alone, using the melting rate as the basis gave a good correlation with the yield. From this relationship, it is possible to calculate the current melting rate and predict the yield online. In addition, by setting a target value for the yield, it is possible to calculate the desired melting rate. Next, the operating conditions were changed to control the melting rate.
溶融率を制御するためには、層内温度（ここではＴｍａｘ）を制御するが必要ある。理想的には複数の条件で焼成モデルを計算して、目的のＴｍａｘとなる条件を提案することが好ましいが、オンラインで制御するためには時間がかかることが課題である。そこで、Ｔｍａｘと相関の高い操業因子を抽出し、下記（６）式の重回帰を構築することで、簡易的に予測する手法を用いた。 To control the melting rate, it is necessary to control the temperature within the layer (Tmax in this case). Ideally, it would be preferable to calculate a firing model under multiple conditions and propose conditions that will result in the desired Tmax, but the challenge is that online control takes time. Therefore, we used a simple prediction method by extracting operational factors that are highly correlated with Tmax and constructing a multiple regression using equation (6) below.
(６)式は一例だが、説明変数には計算温度と相関が高く、特に導入する焼結機の特徴を良く示す因子を入れることがより望ましい。図５に（４）式を用いて計算した温度と、モデルにより計算した温度の関係を示す。比較的精度良く温度を予測することができており、(６)式を用いて溶融率制御を検討した。 Equation (6) is just one example, but it is preferable to include explanatory variables that are highly correlated with the calculated temperature and that particularly reflect the characteristics of the sintering machine being installed. Figure 5 shows the relationship between the temperature calculated using equation (4) and the temperature calculated by the model. The temperature was predicted with relatively high accuracy, and melting rate control was examined using equation (6).
＜（３）歩留の予測について＞
図６に従来法および本手法による歩留の結果を示す。本手法では(６)式を用いて、ｃｏｋｅのアクションを提案した。具体的には、（４）式のｃｏｋｅ以外の説明変数に現状の操業値を入力し、Ｔｍａｘには溶融率が目標値となるような温度を入力して、ｃｏｋｅを逆算した。図６に示すように、歩留のバラつきを低減させ、更に歩留を向上させることに成功した。今回はｃｏｋｅに着目したが、別の説明変数を制御しても良いし、説明変数を追加しても良い。例えば、熱のアクションとしてＬＮＧ、
点火時間の制御としてＰ．Ｓ．、下層の温度を上げるために層厚を上げる、など、様々なアクションが可能である。また、説明変数の追加には例えば、温度に通気が大きく関係するのであれば、風量を入れても良いし、高さ方向の温度分布が効くのであれば、各層の温度やコークスの高さ方向の偏析を入れても良い。
<(3) Yield forecast>
Figure 6 shows the yield results for the conventional method and this method. In this method, we proposed a coke action using equation (6). Specifically, we input the current operating values into the explanatory variables other than coke in equation (4), and input the temperature at which the melting rate becomes the target value into Tmax, and then back-calculated coke. As shown in Figure 6, we succeeded in reducing the variation in yield and further improving it. This time, we focused on coke, but it is also possible to control another explanatory variable, or add an explanatory variable. For example, LNG,
Various actions are possible, such as controlling the ignition time with a P.S. or increasing the layer thickness to raise the temperature of the lower layer. Furthermore, explanatory variables can be added, for example, if ventilation is closely related to temperature, the air volume can be included, or if the temperature distribution in the vertical direction is effective, the temperature of each layer or the segregation of coke in the vertical direction can be included.
＜本発明に係る焼結鉱の製造方法について＞
上述した焼結鉱品質の予測方法の実施により、短時間で焼結鉱溶融率が予測できるので、焼結鉱歩留をオンラインで把握し、管理できるようになる。さらに、予測された焼結鉱溶融率が目標とする歩留つまり焼結鉱溶融率になるように、焼結鉱の製造条件を設定することで、焼結鉱の溶融率を制御でき、歩留の改善および歩留のバラつきの改善が実現できる。
<Regarding the method for producing sintered ore according to the present invention>
By implementing the above-described method for predicting sinter ore quality, the sinter ore melting rate can be predicted in a short time, allowing the sinter ore yield to be grasped and managed online. Furthermore, by setting the sinter ore production conditions so that the predicted sinter ore melting rate becomes the target yield, i.e., the sinter ore melting rate, the sinter ore melting rate can be controlled, thereby realizing improvements in yield and improvement in yield variation.
本発明に係る焼結鉱品質の予測方法によれば、焼結鉱の歩留をオンラインで把握し、管理でき、その焼結鉱溶融率のオンライン予測方法を用いた焼結鉱の製造方法とともに、産業上有用である。 The sinter ore quality prediction method of the present invention allows for online monitoring and management of sinter ore yield, and is industrially useful, along with a sinter ore manufacturing method that uses this online method for predicting the sinter ore melting rate.
１ 焼結鉱の製造設備
２ ドラムミキサー
３ 焼結機
４ 破砕機
５ クーラー
６ 篩分装置
１１ 焼結原料供給装置
１２ パレット台車
１３ 点火炉
１４ ウインドボックス
REFERENCE SIGNS LIST 1 sinter ore manufacturing equipment 2 drum mixer 3 sintering machine 4 crusher 5 cooler 6 sieving device 11 sinter raw material supply device 12 pallet cart 13 ignition furnace 14 wind box
Claims (4)
焼結鉱の製造条件と伝熱モデルとを用いて前記装入層内の焼結温度履歴を算出し、
前記焼結温度履歴から計算される焼結機高さ方向で最も高い温度（Ｔｍａｘ）を求め、
前記焼結機高さ方向で最も高い温度（Ｔｍａｘ）と化学成分を用いて前記焼結鉱の溶融率を予測し、
前記予測した焼結鉱の溶融率から歩留を予測することを特徴とする、焼結鉱品質の予測方法。 A method for predicting the quality of sintered ore produced by charging sintering raw materials into an endless moving pallet cart of a Dwight Lloyd type sintering machine to form a charging bed and sintering the charging bed, comprising:
Calculating the sintering temperature history in the sintering bed using the sintered ore production conditions and a heat transfer model;
The highest temperature (Tmax) in the height direction of the sintering machine calculated from the sintering temperature history is determined,
Predicting the melting rate of the sintered ore using the highest temperature (Tmax) in the height direction of the sintering machine and chemical components;
A method for predicting sintered ore quality, comprising predicting a yield from the predicted melting rate of the sintered ore.
前記焼結鉱品質の予測方法を用いて予測した歩留から、予め定められた焼結鉱の歩留になる焼結鉱の製造条件を求め、
求められた前記製造条件で前記焼結鉱を製造することを特徴とする、焼結鉱の製造方法。
A method for producing sintered ore using the method for predicting sintered ore quality according to any one of claims 1 to 3 ,
determining sinter ore production conditions that result in a predetermined sinter ore yield from the yield predicted using the sinter ore quality prediction method;
A method for producing sintered ore, characterized in that the sintered ore is produced under the determined production conditions.
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| JP2015137368A (en) | 2014-01-20 | 2015-07-30 | 新日鐵住金株式会社 | Calculation method of sintering temperature history |
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| JP2015137368A (en) | 2014-01-20 | 2015-07-30 | 新日鐵住金株式会社 | Calculation method of sintering temperature history |
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