Method for determining the content of at least metallic iron in sponge iron or a sample thereof made from direct reduction of iron ore

Abstract

This invention relates to a method for treating at least metallic iron (Fe) in sponge iron or samples thereof produced by direct reduction of iron ore. met A method for content determination is described. To this end, a mathematical model is provided, whose output variable A is... mod At least metallic iron Fe, described as the sponge iron or a sample thereof met The content is a function of the mathematical model, wherein the mathematical model includes the permeability µ of the sponge iron or a sample thereof. eff and conductivity σ eff The effective medium is approximately EMA.

Description

Technical Field

[0001] This invention relates to a method for determining the content of at least metallic iron in sponge iron or samples thereof produced by direct reduction of iron ore. Background Technology

[0002] To determine the degree of metallization of a measured volume of sponge iron or a sample thereof, the known approach in the prior art (DE3017001A1) involves detecting a measured variable, namely the impedance of a measuring coil coupled to an excitation coil via the sponge iron or sample. The excitation coil applies time-varying magnetic fields of different frequencies to the sponge iron or sample. Therefore, the measured variable is related to at least one electromagnetic property of the sponge iron or a portion thereof. According to DE3017001A1, the impedance of the measuring coil should have a good relationship with both the volume conductivity and the degree of metallization of the sponge iron or sample. A drawback of this method is that the accuracy of the relationship between the measured data and the volume conductivity is not high, and only a rough estimate of the degree of metallization can be made. Therefore, this method is also unsuitable for precise adjustment, for example, in the direct reduction method. Summary of the Invention

[0003] In view of this, the object of the present invention is to improve the accuracy of the method for determining the content of at least metallic iron in sponge iron.

[0004] The solution of the present invention for achieving the above-mentioned objective is characterized by claim 1.

[0005] Not only in determining the content of at least one element in sponge iron or a sample thereof by utilizing the relationship between detected electrical measurement variables and the electromagnetic properties of sponge iron, as disclosed in the prior art, but also by employing a mathematical model for this purpose, the accuracy of the method can be significantly improved. In particular, according to the present invention, a mathematical model is provided whose output variable is described as at least metallic iron (Fe) in sponge iron or a sample thereof. met The mathematical model is a function of the content of ), where the mathematical model includes the permeability ( ) of sponge iron or its sample. ) and conductivity ( The effective medium approximation (EMA) for permeability and conductivity is used. That is, unexpectedly, by means of the effective medium approximation (EMA) for permeability and conductivity, at least metallic iron (Fe) is implemented using the detected measurement variables and the mathematical model. met The estimation method for determining the content of iron ore can be performed significantly more accurately and / or more quickly. Therefore, the rapid and accurate method of the present invention is also particularly suitable for monitoring, adjusting, and controlling the process of direct reduction of iron ore.

[0006] Preferably, the mathematical model includes the gangue ratio of sponge iron or its sample in iron ore ( pg ) as the first input parameter, and / or the effective density of sponge iron or its sample, in particular ( ) is used as the second input parameter.

[0007] If the gangue percentage is preset as the first input parameter, the inaccuracy of the content determination can be further reduced because these measures allow for a more precise determination of the iron content (metallic iron, iron oxide, iron carbide) in the solid content of the measured volume. Preferably, the gangue percentage can be a variable input parameter, derived from the iron ore used and applicable to the mathematical model. This can further improve the accuracy of the method. The density of the sponge iron or its sample, as the second input parameter, can be determined, for example, by weighing or by measuring the iron ore used in a simple procedure. This allows for the precise determination of the gas content, and (since the magnetic and electrical parameters of the gas content are known) the content determination can be performed with particular precision and strong resistance to interference factors. Preferably, the density can be a variable input parameter, derived from the iron ore used and applicable to the mathematical model. This can further improve the accuracy of the method.

[0008] If the mathematical model is an electromagnetic model (EMM), the accuracy of the method can be further improved. This is particularly because the modeling variables can more accurately map the electrical measurement variables.

[0009] If the model output variables A mod electrical impedance Z mod ( This allows for better determination of magnetic and non-magnetic substances / materials, such as metallic iron (Fe). met The proportions of iron oxide (FeO) and iron carbide (Fe3C).

[0010] Preferably, the impedance model includes modeling at least one electric coil using sponge iron or a sample thereof as the core material.

[0011] If we consider the voltage formed at the impedance model or modeling impedance, especially considering the known applied current. U mod ( By modeling, model parameters can be determined for the proportions of magnetic and non-magnetic materials, such as iron and / or iron oxide and / or iron carbide, which can further improve the accuracy of the method.

[0012] Alternatively, the current formed at the impedance model or modeled impedance when a known voltage, especially an external voltage, is applied can be used. I mod ( Modeling is performed.

[0013] Unlike existing technologies, this method uses estimation to determine at least one detected measurement variable (A). mess ) and the model output variables of the mathematical model (A) mod When the deviation of one or more contents is minimized, particularly accurate content determination can be achieved. Preferably, the detected measurement variable (A) is determined by estimation. mess The sum of ) and the model output variable (A) of the mathematical model mod The least squares estimation method minimizes the deviation of one or more contents. In other words, this estimation method can provide an extremely sensitive stochastic process, thereby reducing the workload of actual data detection. Thus, for example, applying two magnetic fields is sufficient to detect enough measured data to infer the content of metallic iron and / or iron oxide and / or iron carbide in sponge iron with extremely high accuracy. The least squares estimation method is particularly suitable for this purpose.

[0014] Preferably, as or for measurement variable A mess For the coil supplied with external current I The generated magnetic field induces voltage U mess The test is conducted in which the coil has sponge iron or a sample thereof as the core material.

[0015] Alternatively, as or for the measurement variable A mess When an external current U is applied to the coil, the current I formed in this coil is... mess The test is conducted in which the coil has sponge iron or a sample thereof as the core material.

[0016] The accuracy of the method can be further improved by detecting first measurement data of the measured variable through a first magnetic field in the induction sponge iron or its sample, and second measurement data of the measured variable through a second magnetic field induction in the induction sponge iron or its sample, wherein the magnetic fields vary with time and have different frequencies. Accuracy can be further improved by detecting other measured data at other frequencies.

[0017] Preferably, the model output variable (A) mod ) can be described as sponge iron or its sample (4) of at least metallic iron (Fe) met The content of at least one iron oxide (Fe2O3, Fe3O4, or FeO) and iron carbide (Fe3C) is a function of the measured values. This allows for the implementation of measurements on at least metallic iron (Fe3C) using the detected measurement variables and mathematical models. met An estimation method for determining the content of iron oxide (Fe2O3, Fe3O4 or FeO) and iron carbide (Fe3C). Attached Figure Description

[0018] The invention's subject matter is illustrated in detail in the figures, for example, with reference to embodiments. Figure 1 A simplified diagram of mathematical model 1 is shown, and Figure 2 This is a schematic diagram of the measuring equipment. Detailed Implementation

[0019] Will Figure 1 Mathematical Model 1 and Electrical Measurement Variables U mess Together used to determine metallic Fe met content p FeMet Determination of the content of iron oxide (FeO) p FeO And the determination of the content of iron oxide (Fe3C). p Fe3C .

[0020] Mathematical Model 1 describes the content of sponge iron or its sample 4 relative to metallic iron. p FeMet , content of iron oxide (FeO) p FeO and the content of iron oxide (Fe3C) p Fe3C Related electromagnetic properties. Among them, p i ( i ={FeMet, Fe0, Fe3O4, ...}) refers to the mass in terms of the total mass of the material in the sample container, for example... p FeMet This refers to metallic iron (Fe) in terms of the total mass of the material in the sample container. met The quality.

[0021] In addition, the quality estimation of direct reduced iron (DRI) typically also considers the quality of iron oxide and iron carbide. Based on the composition of the raw materials used, DRI also includes gangue. Overall, the material to be examined constitutes a significant portion of the total mass. p i Metallic iron Fe met The mass percentage of iron oxide and iron carbide, and the total mass of gangue, is as follows: p g The composition of iron-free substances.

[0022] The proportion of gangue can be determined using various methods (such as chemical analysis). p g Or, if the proportion of the vein stones p gKnown as typical characteristic parameters of raw materials in certain mining areas, the mass of gangue can be determined, from which the total mass of iron, iron carbide, and iron oxide within that volume can be calculated. Finally, the mathematical model must separate the proportion of metallic iron from the mass of the remaining components. According to the invention, this is carried out based on the electromagnetic properties of the different components.

[0023] In a preferred technology variant Figure 2 The measuring device 100 shown includes a coil 101 in the form of a cylindrical coil, which surrounds sponge iron or a sample 4 therefrom, thereby serving as a core material. Figure 2 The coil shown can be replaced by a combination of one or more excitation coils with one or more measuring coils, which is not detailed here.

[0024] A simplified impedance model 3 is obtained from this measuring device. This model is derived from the analysis of the impedance of a uniform cylinder, in which its electromagnetic properties are affected by the iron content.

[0025] Measurement Variables U mess The relationship with the electromagnetic properties of sample 4 is derived from the solution of electromagnetic circuit 4. That is, in addition to the electromagnetic properties of sample 4, the geometry of the device and the electrical characteristics of the measuring device (such as the diameter of cylindrical coil 101 and the resistance of coil 101) also have an impact. This basic processing method will be explained further.

[0026] According to one embodiment, sample material is fed into an elongated cylindrical, non-magnetic, and non-conductive container. A short loop coil 101 is arranged around this container, which can be used as both an excitation coil and a measurement coil.

[0027] For the modeling of impedance model 3, the model impedance of this embodiment of the measurement configuration can be considered. Z Simply assume the sample volume is an approximately infinitely long cylinder compared to the height of the measuring coil, and the measuring system is a cylindrical coil enclosing this volume (see H. Libby, Introduction to Nondestructive Electromagnetic Testing Methods, Wiley, 1971). This allows us to utilize electromagnetic mathematical models (EMM).

[0028] in angular frequency of the applied alternating current Effective permeability of sample volume The average radius of the sample volume The average radius of the b-cylinder coil ber(k*a) is the real part of the Kelvin-Bessel function. The 1-derivative of ber'(k*a)ber(k*a) bei(k*a) is the imaginary part of the Kelvin-Bessel function. The 1-derivative of bei'(k*a)bei(k*a) Numerical characteristics of the k-eddy current problem as well as

[0029] in angular frequency of the applied alternating current Effective permeability of sample volume conductivity of sample volume Electric field constant (8.854 10) -12 As / Vm) To measure the impedance of the system Z Modeling.

[0030] To refine the mathematical model 1 used for content determination, thereby obtaining a mathematical model for material distribution, mathematical model 1 includes the effective magnetic permeability for sponge iron or its sample 4. and effective conductivity The effective medium approximation (EMA2) is based on the principle of establishing a mathematical relationship between effective material properties and each component and its volume fraction.

[0031] For simplicity, in this embodiment, it is assumed that sample 4 consists of two material phases, one being metallic iron (Fe). met That is, the first part is a ferromagnetic material with good electrical conductivity, while the remaining part is a weakly ferromagnetic material with extremely poor or no electrical conductivity. In other words, it is assumed here that the volume fraction f is... FeMet Metallic iron Fe met It is a ferromagnetic material with good electrical conductivity, and the sum of iron oxide, gangue and air is a weak ferromagnetic material with relatively poor electrical conductivity.

[0032] Therefore, according to the aforementioned embodiment, when measuring metallic iron (Fe) met The volume-related percentage f of the sample volume FeMet In this case, only an inverse Maxwell-Garnett formula for both material phases is needed (see J.C. Maxwell-Garnett, Color in Metallic Glasses and Thin Films, Trans. Royal Soc. London, Vol. 203, pp. 385-420, 1904).

[0033] in The known permeability of pure iron (the permeability of magnetic flux density below 0.9 T is approximately 5000 in the frequency range up to 100 Hz). Unknown permeability of nonferromagnetic materials Total effective permeability of the material The expected volume fraction of metallic iron (Femet) Similarly, the effective electrical conductivity of the material is determined in a similar manner. Modeling. In this case, the inverse Maxwell-Garnett formula for two material phases is:

[0034] in The known conductivity of pure iron (approximately 10 Sm / mm in the frequency range up to 100 Hz) 2 ), The electrical conductivity of non-ferromagnetic materials with relatively poor electrical conductivity.

[0035] In a further simplification, we can assume that this conductivity is zero.

[0036] The total effective conductivity of the material Expected volume percentage of metallic iron Depending on the specific type of raw material, various EMAs are available for modeling two-phase or multiphase material mixtures based on their material mixing, spatial distribution, and geometric proportions. For example, if it is necessary to determine not only metallic iron (Fe), but also... met percentage p FeMet It is also necessary to determine the proportion of other metals or conductive materials, especially iron oxide and / or iron carbide, for which a modeling method for multiphase material mixtures can be selected (e.g., AH Sihvola and IV Lindell, Effective permeability of mixtures, Prog Electromagn Res. 06, pp. 153-180, 1992).

[0037] These formulas typically do not use the mass-related content of each component. p i Instead of estimating effective electromagnetic variables, volume-related variables are used. f i This can be achieved by using the material density and the total effective density of the sample container. Let's do the conversion.

[0038]

[0039] In mathematical model 1, the effective density of sample 4 can be... The proportion of vein stones p g Modeling as input parameters. This is typically implemented, for example, using known values ​​of the base material used. However, the proportion of gangue p in the sample container can also be determined very accurately. g and relative density Specifically, the proportion and relative density of the gangue are calculated using the pre-determined mass of the material of sample 4 and the known volume of the sample container.

[0040] Utilizing the effective permeability relative to the sample volume ( ) and the conductivity of the sample volume ( The result contains two unknowns: the permeability of the nonferromagnetic material (…). The EMA equation, which describes the expected volume fraction of metallic iron, can be used to determine the Fe content of sponge iron or sample 4. met Volume ratio f FeMet .

[0041] Since different models cannot be explicitly applied to each other in multiphase material mixtures, numerical estimation methods can be used to solve the overall model. One possible method is the least squares estimation method. The least squares estimation method can be used to determine the modeling variable A. mod With electrical measured A mess The deviation has a minimum value for metallic iron (Fe). met The content of ) also applies to sample 4 in the corresponding mathematical model 1. Figure 1 Iron oxide (FeO) is optionally shown in the image. Figure 1 Iron carbide (Fe3C) is optionally shown in the image, wherein... Figure 1 It can be identified at the dotted line.

[0042] In other words, if the complex impedance is known, the effective permeability and effective conductivity of the material can be calculated, and the volume composition combination can then be calculated using the EMA.

[0043] The complex impedance of the measurement system can be determined by the current measured when a defined voltage is applied or the voltage measured when a defined current is introduced.

[0044] Suitable as a measurement output variable for implementing the measurement process ( A mess ) and model output variables ( A modIn particular, there is the induced voltage in the coil. U mess , U mod ), Measurement configuration of complex impedance ( Z mess , Z mod ) or by measuring or exciting the current in the coil ( I mess , I mod ).

[0045] In a preferred embodiment, impedance is used as the model output variable A. mod Modeling, i.e. A mod impedance Z mod The steps of the method are arranged in the following order: a. Provide a mathematical model. The model describes the relationship between the sample 4 of the sponge iron in the measurement circuit and the electrical frequency. Sponge iron or metallic iron (Fe) of sample 4 met The impedance related to the content of iron oxides (Fe2O3, Fe3O4, or FeO) and iron carbide (Fe3C) Z mod ( ).

[0046] Regarding this description, mathematical model 1 includes, on the one hand, the relationship between the magnetic permeability (…) and the magnetic permeability of sponge iron or its sample 4. ) and conductivity ( The model includes the determination of impedance related to sponge iron (Fe). On the other hand, the model includes the determination of impedance related to sponge iron (Fe). met The content of iron oxides (Fe2O3, Fe3O4, or FeO) and iron carbide (Fe3C), as well as the permeability related to the gangue ratio and density, are considered. ) and conductivity ( For the determination of ), the effective medium approximation (EMA) is applied.

[0047] b. The effective density of sample 4 The proportion of gangue in sample 4 (p) g Applied to mathematical model 1.

[0048] c. Place sample 4 of sponge iron into the magnetic circuit of the measurement configuration.

[0049] d. The first current curve I ( An external voltage is applied to the excitation coil, and the voltage is measured based on the first voltage curve on the measuring coil. U mess ( The impedance is determined / detected by measurement. Z mess ( ) as a measurement variable (A) mess ).

[0050] e. The second current curve I ( An external voltage is applied to the excitation coil, and the second voltage curve on the measuring coil is used as a reference. U mess ( The impedance is determined / detected by measurement. Z mess ( ) as a measurement variable (A) mess ).

[0051] f. Optionally: Other current curves I ( An external voltage is applied to the excitation coil, and the voltage is measured based on other voltage curves on the measuring coil. U mess ( ) measurement to determine / detect Z mess ( ) as a measurement variable (A) mess ).

[0052] g. Apply the least squares estimation method, using mathematical model 1 and the voltage curve. U mess ( ), U mess ( ) and optional U mess ( The measured data were used to determine the metallic iron (Fe) in sample 4 of the sponge iron. met The proportions of iron oxides (Fe2O3, Fe3O4 or FeO) and / or iron carbide (Fe3C).

[0053] Among them, the variables used as model output variables in sample 4 were determined. A mod Modeling impedance Z mod With as a measurement variable (A) mess ) measured impedance Z mess The metal with the smallest sum of deviations is iron (Fe). met The proportion of iron oxides (Fe2O3, Fe3O4 or FeO) and / or iron carbide (Fe3C).

[0054] In an alternative implementation, a voltage curve U( ) may also be applied to the excitation coil in steps d.-f. ), and the current curve formed in the measuring coil. I mess ( ) Measure the impedance Z mess ( ).

[0055] In another preferred embodiment, voltage is used as the model output variable A. mod The modeling involves induction through an externally defined current curve, meaning the modeling variable is... A mod For voltage U mod The steps of the method are arranged in the following order: a. Provide a mathematical model describing the measurement circuit containing sample 4 of sponge iron or metallic iron (Fe) of sample 4. met The voltage related to the content of iron oxides (Fe2O3, Fe3O4, or FeO) and iron carbide (Fe3C). U mod ( , I Regarding this description, mathematical model 1 includes, on the one hand, the relationship between the magnetic permeability and the properties of sponge iron or its sample 4. ) and conductivity ( The model includes the determination of impedance related to sponge iron (Fe). On the other hand, the model includes the determination of impedance related to sponge iron (Fe). met The content of iron oxides (Fe2O3, Fe3O4, or FeO) and iron carbide (Fe3C), as well as the permeability related to the gangue ratio and density, are considered. ) and conductivity ( For the determination of ), the effective medium approximation (EMA) is applied.

[0056] b. The effective density of sample 4 The proportion of gangue in sample 4 (p) g Applied to mathematical model 1.

[0057] c. Place sample 4 of sponge iron into the magnetic circuit of the measurement configuration.

[0058] d. The first current curve I ( An external voltage is applied to the excitation coil, and the first voltage curve is measured / detected. U mess ( ) as the measured variable on the measuring coil (A) mess).

[0059] e. The second current curve I ( An external voltage is applied to the excitation coil, and the second voltage curve is measured / detected. U mess ( ) as the measured variable on the measuring coil (A) mess ).

[0060] f. Optionally: Other current curves I ( An external voltage is applied to the excitation coil, and other voltage curves are measured / detected. U mess ( ) as the measured variable on the measuring coil (A) mess ).

[0061] g. Apply the least squares estimation method, using mathematical model 1 and the voltage curve. U mess ( ), U mess ( ) and optional U mess ( The measured data were used to determine the metallic iron (Fe) in sample 4 of the sponge iron. met The proportions of iron oxides (Fe2O3, Fe3O4 or FeO) and / or iron carbide (Fe3C).

[0062] Among them, the variables used as model output variables in sample 4 were determined. A mod Modeling voltage U mod With as a measurement variable (A) mess ) measured voltage U mess The metal with the smallest sum of deviations is iron (Fe). met The proportion of iron oxides (Fe2O3, Fe3O4 or FeO) and / or iron carbide (Fe3C).

[0063] Therefore, by means of the approximate permeability of mathematical model 1 and impedance model 3, which take into account the above content. and conductivity Furthermore, it is preferable to utilize known parameters for effective density. proportion of vein stones p g This allows for the processing of sponge iron or metallic iron (Fe) in sample 4. met), optional iron oxide (FeO) and optional iron carbide (Fe3C) are used to perform particularly precise content determination.

[0064] Generally speaking, "in particular" can be translated as "more particularly" in English. Features preceded by "in particular" can be considered optional features, which can be omitted and therefore do not constitute a limitation on the claims, for example. The same applies to "preferably," which is translated as "preferably."

Claims

1. A method for determining the content of at least metallic iron in sponge iron or a sample (4) of iron ore produced by direct reduction of iron ore, the method comprising the following steps: At least one electrical measurement variable is detected, said measurement variable being related to at least one electromagnetic property of the sponge iron or its sample (4). A mathematical model (1) is provided, the output variables of which are described as a function of the content of at least metallic iron in the sponge iron or the sample (4) therein, wherein the mathematical model (1) includes an effective dielectric approximation for the magnetic permeability and electrical conductivity of the sponge iron or the sample (4). An estimation method for determining the content of at least metallic iron is implemented using the detected measurement variables and the mathematical model (1).

2. The content determination method according to claim 1, characterized in that, The mathematical model (1) includes the gangue ratio of the iron ore of the sponge iron or its sample (4) as the first input parameter, and / or the density of the sponge iron or its sample (4) as the second input parameter.

3. The content determination method according to claim 1, characterized in that, The mathematical model (1) is an electromagnetic model, which includes an impedance model (3).

4. The content determination method according to claim 3, characterized in that, The impedance model (3) includes modeling at least one coil (101) with the sponge iron or a sample of it (4) as the core material.

5. The content determination method according to claim 3 or 4, characterized in that, The output variable of the model is electrical impedance.

6. The content determination method according to any one of claims 3 or 4, characterized in that, The model output variable takes into account the known current. I The voltage formed at the impedance model (3) U mod ( ).

7. The content determination method according to any one of claims 3 or 4, characterized in that, The output variable of the model is the current formed at the impedance of the impedance model (3) when a known voltage is applied. I mod ( ).

8. The content determination method according to claim 1, characterized in that, The estimation method is used to determine the content of at least one or more of the detected measured variables that have the smallest deviation from the model output variable of the mathematical model (1).

9. The content determination method according to claim 1, characterized in that, As a variable to be measured, the applied current in coil (101) is used to measure the variable. I The generated magnetic field induces voltage U mess The test is performed, wherein the coil (101) has the sponge iron or a sample (4) thereon as the core material.

10. The content determination method according to claim 1, characterized in that, As a variable to be measured, the applied current at coil (101) is... U Current formed at time I mess The test is performed, wherein the coil (101) has the sponge iron or a sample (4) thereon as the core material.

11. The content determination method according to claim 1, characterized in that, The first measurement data of the measured variable is detected by applying a first magnetic field to the sponge iron or its sample (4), and the second measurement data of the measured variable is detected by applying a second magnetic field to the sponge iron or its sample (4), wherein the magnetic field varies with time and has different frequencies.

12. The content determination method according to claim 1, characterized in that, The model output variable is described as a function of the content of at least metallic iron and at least one iron oxide and iron carbide in the sponge iron or its sample (4), and the estimation method for determining the content of at least metallic iron, iron oxide and iron carbide is implemented using the detected measurement variable and the mathematical model (1).

13. The content determination method according to claim 8, characterized in that, The estimation method described is the least squares estimation method.

Images