Method for controlling the suction of process gas in an electric arc furnace and related steel production plant

Abstract

A method for controlling the suction of process gas emitted by an electric arc furnace (20) inside its vessel (22) during operation comprises an adjustment step of adjusting the flow rate (Y) of the process gas sucked in, based on the value of at least one parameter, said at least one parameter comprising the flow rate (X2) of carbonaceous substance added inside said vessel (22) during the operation of said electric arc furnace (20).

Description

Technical Field

[0001] This invention relates to a method for controlling the extraction of process gases emitted from the vessel of an electric arc furnace (EAF) during operation. Background Technology

[0002] Currently, steel can be produced via two main manufacturing routes. The most commonly used route today, known as the "BF-BOF route," involves producing molten iron in a blast furnace (BF), reducing iron oxide using a reducing agent (primarily coke), and then converting the molten iron into steel in a converter process or a basic oxygen converter (BOF). This route releases significant amounts of CO2, both during the coking process from coal to coke and during the iron production process.

[0003] The second main route involves the so-called "direct reduction method." This includes methods according to brands such as MIDREX®, FINMET®, ENERGIRON® / HYL, COREX®, and FINEX®, in which sponge iron is produced from the direct reduction of an iron oxide carrier in the form of HDRI (hot direct reduced iron), CDRI (cold direct reduced iron), or HBI (hot briquetted iron). The sponge iron in HDRI, CDRI, and HBI forms is then further processed in EAF (Extractable Iron Forming) to produce steel.

[0004] Therefore, one of the main options chosen by steel manufacturers to reduce CO2 emissions is the shift from the BF-BOF route to the DRI-EAF route. However, there are some limitations to using DRI products with ferrous scrap in classic electric arc furnaces. In reality, the scrap contains a significant amount of impurities, and the resulting molten steel will require further processing to produce high-quality steel grades. Furthermore, electric arc furnaces have so far been primarily used to produce specific steel grades, mainly for long product applications, whose metallurgical limitations differ from those of steel grades specifically used in automotive products.

[0005] Compared to the vessel of a BOF (Boiler-Off-Fuel) furnace, the vessel of an EAF (Electric Arc Furnace) furnace has more openings communicating with the surrounding atmosphere (e.g., due to the presence of a movable furnace top, electrode holes, slag doors, etc.). These openings allow air to enter the vessel. This air ingress has several disadvantages. It promotes nitrogen uptake in the molten pool, which can result in a final nitrogen content that does not meet the requirements of the final product. For example, liquid steel produced by a basic oxygen converter contains 20 parts per million (ppm) to 90 ppm of nitrogen by weight, compared to 100 ppm to 140 ppm by weight of liquid steel produced in an electric arc furnace. Therefore, the nitrogen content of current electric arc furnace (EAF) steel is much higher than that of basic oxygen converter (BOF) steel and fails to meet the requirements for high-grade steel. High nitrogen content can lead to inconsistent mechanical properties in hot-rolled steel, embrittlement of the heat-affected zone (HAZ) in welded steel, and poor cold formability. Air ingress also leads to heat loss and constitutes an additional input of oxygen into the vessel. This oxygen can promote the oxidation of iron, resulting in iron loss in the slag.

[0006] EAF containers typically include process gas extraction devices. If left unregulated, these devices can either cause excessive air to enter the container (in the event of negative pressure) or cause excessive release of process gases and dust around the EAF (in the event of overpressure).

[0007] Document US4450003 describes a method for controlling suction based on parameters of the intake exhaust gas. However, this method lacks accuracy because the temperature of the exhaust gas and the interactions between its different components make chemical analysis difficult. The instantaneous flow rate of these exhaust gases is also difficult to measure due to rapid pressure fluctuations caused by suction elements such as fans and valves. Furthermore, since the analysis of the intake exhaust gas must be performed downstream of the suction device, there is a delay between gas formation and suction regulation. Summary of the Invention

[0008] One of the objectives of this invention is to address this problem by proposing a method for controlling the extraction of process gases within an EAF vessel, which enables optimal protection of the liquid steel from air ingress while limiting the energy consumed and restricting leakage of process gases around the vessel.

[0009] Therefore, the present invention relates to a method for controlling the extraction of process gases emitted from the vessel of an electric arc furnace during operation.

[0010] The method includes a regulating step of adjusting the flow rate of the intake process gas based on the value of at least one parameter, the at least one parameter including the flow rate of carbonaceous material added into the vessel during operation of the electric arc furnace.

[0011] Thanks to these features, the flow rate of the intake gas is adjusted based on the flow rate of the process gas discharged from the container. In fact, the flow rate of the process gas discharged from the container is essentially proportional to the flow rate of the carbonaceous material added to the container. In reality, the carbonaceous material added to the container (e.g., via a carbon gun and / or gas burner) is likely to be converted into CO and / or CO2. Therefore, taking into account the flow rate of the carbonaceous material added to the container, increases or decreases in the generated process gas flow rate can be predicted, thereby adjusting the extraction of the process gas to avoid creating a negative or overpressure state in the internal volume of the container.

[0012] The method may also include the following features, which may be considered individually or in any technically feasible combination:

[0013] - The carbonaceous material added to the container during the operation of the electric arc furnace includes carbonaceous gas, which is added to the container via a gas burner and / or a carbon lance;

[0014] - The adjustment steps ensure that during operation of the electric arc furnace, the gas pressure inside the container is substantially equal to atmospheric pressure minus 0.15 mBar;

[0015] - The method includes a determination step for determining the value of at least one parameter;

[0016] - The operation of the electric arc furnace takes place over a period of time, and the adjustment steps are performed at several adjustment moments within that period of time;

[0017] - The value of at least one parameter in the adjustment step at each adjustment time is the current actual value of at least one parameter at that adjustment time;

[0018] - The adjustment steps are also based on a machine learning model that takes into account:

[0019] - Multiple previous values ​​of at least one parameter at a previous adjustment time during at least the previous operation of the electric arc furnace;

[0020] - The corresponding flow rate of the intake process gas, as a function of multiple previous values; and

[0021] - The adjustment step is also based on the value of at least one additional parameter, which includes at least one of the following:

[0022] - An electrical parameter representing the current flowing through the electrodes of an electric arc furnace during operation;

[0023] - Mechanical parameters representing the mechanical waves generated within the vessel during the operation of the electric arc furnace;

[0024] - Temperature of the container walls and / or furnace top;

[0025] - The pressure representing the process gas pressure, which corresponds to the pressure difference between the pressure inside the container and atmospheric pressure;

[0026] - At least one flame parameter representing the flame generated within the container, said at least one flame parameter including, for example, flame temperature and / or flame size; and

[0027] - Chemical parameters representing the component properties of process gases.

[0028] The present invention also relates to steel production facilities, which include at least:

[0029] - An electric arc furnace, including a container and at least one means for adding a carbonaceous material into the container during operation of the electric arc furnace;

[0030] - Equipment for extracting process gases emitted from the vessel of an electric arc furnace during operation, said equipment comprising:

[0031] - A device for drawing gas from a container;

[0032] - At least one sensor configured to generate data representing at least one parameter, said at least one parameter including the flow rate of carbonaceous material added into the container;

[0033] - A control module adapted to receive data representing at least one parameter and configured to adjust the suction flow rate of the gas suction device based on at least one parameter.

[0034] The steel production facility may also include the following features, either individually or in any technically feasible combination:

[0035] - The carbonaceous material added to the container during operation of the electric arc furnace includes carbonaceous gas, and the at least one carbonaceous material adding device includes a gas burner and / or a carbon lance;

[0036] - The control module is configured to adjust the suction flow rate of the gas suction device so that during the operation of the electric arc furnace, the gas pressure inside the container is basically equal to atmospheric pressure minus 0.15 mBar.

[0037] - The electric arc furnace is designed to operate within a time period, and the control module is configured to adjust the suction flow rate of the gas suction device at several adjustment times within that time period;

[0038] - The control module is configured to adjust the suction flow rate of the gas suction device at each adjustment time based on the current actual value of at least one parameter at the adjustment time; and

[0039] - The control module is configured to adjust the suction flow rate of the gas suction device at each adjustment time based on a machine learning model, which takes into account:

[0040] - Multiple previous values ​​of at least one parameter at a previous adjustment time during at least the previous operation of the electric arc furnace;

[0041] - The value of the corresponding flow rate of the intake process gas as a function of multiple previous values. Attached Figure Description

[0042] Other aspects and advantages of the invention will become apparent after reading the following description, which is given by way of example and with reference to the accompanying drawings, in which:

[0043] - Figure 1 This is a schematic cross-sectional view of a portion of a steel production facility according to an embodiment of the present invention; and

[0044] - Figure 2 This is a schematic diagram of a method for controlling the extraction of process gas emitted from an EAF container according to an embodiment of the present invention. Detailed Implementation

[0045] In the following text, unless otherwise stated, all traffic volumes refer to quality traffic.

[0046] refer to Figure 1 The steel production facility 10 according to the present invention is described.

[0047] The steel production facility 10 includes at least an electric arc furnace 20 (EAF) and equipment 60 for extracting process gases emitted from its container 22 during operation of the EAF 20.

[0048] EAF 20 is designed to receive metallic materials to be melted.

[0049] EAF 20 is designed to operate over a period of time.

[0050] EAF 20 includes a container 22 defining an internal volume 24 into which metallic material is introduced. For example... Figure 1 As shown in the example, container 22 includes a bottom wall 26, side walls 27, and a removable furnace top 28, which is designed to cooperate with the side walls 27 and the bottom wall 26 to define an internal volume 24.

[0051] For example, the metallic material includes scrap steel, such as steel with pig iron and / or direct reduced iron (DRI). For example, the scrap steel that can be used is referred to as old scrap (E1 or E3), new scrap (E8), shredded scrap (E40), or fragmented scrap (E46) in the EU-21 scrap steel specification. In a preferred embodiment, the metallic material melted into the EAF contains at least 40% DRI by weight, preferably 40% to 60% DRI by weight. For example, the DRI contains 0% to 2.5% carbon by weight.

[0052] The percentage of DRI and / or pig iron in the charge is highly dependent on the quality of the scrap steel available and the type of steel to be produced. If the levels of impurities such as copper, chromium, molybdenum, nickel, tin, antimony, zinc, and / or arsenic are low, the amount of scrap to be charged can be increased, thereby reducing the amount of DRI.

[0053] EAF includes at least one device 30 for loading metallic material into the internal volume 24.

[0054] EAF 20 also includes at least one device 42 for adding carbonaceous material into container 22 during EAF 20 operation.

[0055] The EAF 20 also includes at least one electrode 38 and a cooling system 50.

[0056] At least one metal material adding device 30 is configured to add metal material within container 22 (i.e., within internal volume 24) at a flow rate X1. Advantageously, the flow rate X1 is such that the flow rate of the DRI added to internal volume 24 is from 50 tons / hour to 300 tons / hour, for example, for a duration substantially equal to 30 minutes. For example, at least one metal material adding device 30 includes a metal material source 32 (e.g., a hopper) and advantageously includes a hopper 34 designed to guide the metal material from the source 32 to internal volume 24.

[0057] At least one electrode 38 is arranged to extend at least partially within the internal volume 24 to generate an electric arc that radiates heat within the internal volume 24. For this purpose, the electrode 38 is electrically connected to a power source (not shown) and extends at least partially within the internal volume 24. The electrode 38 preferably operates using CO2-neutral electricity, which in particular includes electricity from renewable energy sources, defined as energy generated from renewable resources that are naturally replenished on a human timescale, including sources such as sunlight, wind, rain, tides, waves, and geothermal energy. In some embodiments, electricity from nuclear sources may be used because it does not emit CO2 during its production.

[0058] According to one embodiment, the electrode 38 is movable relative to the internal volume 24, such that the height of the electrode 38 extending within the internal volume 24 is adjustable.

[0059] like Figure 1 As shown in the example, the EAF 20 includes several parallel electrodes 38. The multiple electrodes 38 are specifically configured for an EAF powered by alternating current. When the electric arc furnace is powered by direct current, a single top electrode can be used in conjunction with at least one bottom electrode.

[0060] At least one carbonaceous material adding device 42 is configured to add carbonaceous material within container 22 (i.e., within internal volume 24) at a flow rate X2. For example, the flow rate X2 is from 0 kg / min to 400 kg / min. Advantageously, the flow rate X2 depends on the dimensions of internal volume 24 and is expressed in kg / min / t, where the flow rate unit takes into account the weight (in tons) of metallic material that can be added to internal volume 24. For example, the flow rate X2 is from 0 kg / min / t to 2.66 kg / min / t, preferably substantially equal to 1.5 kg / min / t. For example, at least one carbonaceous material adding device 42 includes at least one gas burner 44 and / or at least one carbon gun 46.

[0061] At least one gas burner 44 is configured to assist the electrode 38 in melting metallic material by providing additional energy within the internal volume 24. At least one gas burner 44 is designed to add a carbonaceous material (e.g., natural gas) within the container 22 at a flow rate X2A. Advantageously, the flow rate X2A depends on the size of the internal volume 24 and is expressed in Nm³. 3 / h / t indicates that the flow rate unit takes into account the weight (in tons) of metal material that can be added to the internal volume 24. For example, the flow rate X2A for each gas burner 44 is 0 Nm³. 3 / h / t to 5 Nm 3 / h / t, preferably, the flow rate of each gas burner 44 x 2A is approximately equal to 4 Nm 3 / h / t.

[0062] At least one carbon gun 46 is configured to add carbon-containing gas within the internal volume 24 to control foam slag and secondary combustion. The at least one carbon gun 46 is designed to add carbon-containing material into the container 22 at a flow rate X2B. Advantageously, the flow rate X2B depends on the size of the internal volume 24 and is expressed in kg / min / t, where the flow rate unit takes into account the weight (in tons) of metallic material that can be added into the internal volume 24. For example, the flow rate X2B for each carbon gun is from 0 kg / min / t to 2.66 kg / min / t, preferably, the flow rate X2B for each carbon gun is substantially equal to 0.5 kg / min / t.

[0063] The cooling system 50 includes a network of cooling pipes 52 integrated within the walls 26, 27 and / or the furnace roof 28 of the container 22. The cooling pipe network 52 is designed to allow a cooling fluid (e.g., water) to circulate within the walls 26, 27 and / or the furnace roof 28 of the container 22. The cooling fluid is designed to dissipate heat from within the container 22.

[0064] The process gas extraction device 60 (also commonly referred to as a primary dust removal system or device) includes a means 62 for extracting gas from container 22, at least one sensor 70, advantageously at least one additional sensor 72, and a control module 80.

[0065] The gas extraction device 62 is designed to extract process gas from container 22 at a flow rate Y. For example, the flow rate Y is 50,000 Nm³. 3 / h to 200,000 Nm 3 / h, especially for an EAF with a capacity of 150 tons. Typically, the flow rate Y is approximately equal to 150,000 Nm³. 3 / h.

[0066] For example, such as Figure 1 As shown, the gas suction device 62 includes a conduit 64 in fluid communication with the internal volume 24. Advantageously, the gas suction device 62 also includes a fan 66 in fluid communication with the conduit 64. For example, the flow rate Y of the suction gas depends on the suction power of the fan 66 and / or the configuration of the valves of the gas suction device 62 (e.g., arranged within the conduit 64).

[0067] At least one sensor 70 is configured to generate data representing at least one parameter.

[0068] The at least one parameter includes the flow rate X2 of the carbonaceous material added to the container 22 via at least one carbonaceous material addition device 42. The flow rate X2 advantageously includes flow rates X2A and X2B of the carbonaceous material added via at least one gas burner 44 and via at least one carbon lance 46, respectively. The carbonaceous material added to the container 22 during EAF 20 operation includes carbonaceous gas added to the container via at least one gas burner 44 and / or at least one carbon lance 46. Adding carbonaceous material to the container 22 results in an increase in the flow rate of the generated process gas. Specifically, the added carbon reacts with oxides present in the metallic material to form carbonaceous gas, such as CO.

[0069] Advantageously, at least one parameter also includes the flow rate X1 of the metal material added into the container 22 via at least one metal material adding device 30. Based on the flow rate X1 and the carbon content by weight in the added metal material, the flow rate of the carbonaceous material added into the container 22 via at least one metal material adding device 30 can be derived.

[0070] For example, at least one sensor 70 includes at least one carbonaceous material addition sensor 70A configured to generate data representing the flow rate of carbonaceous material added to container 22 via at least one carbonaceous material addition device 42. For example, at least one carbonaceous material addition sensor 70A includes a first sensor 70A1 configured to generate data representing the flow rate of carbonaceous material added to container 22 via at least one gas burner 44, and a second sensor 70A2 configured to generate data representing the flow rate of carbonaceous material added to container 22 via at least one carbon gun 46.

[0071] Advantageously, at least one sensor 70 also includes at least one metal material addition sensor 70B, which is configured to generate data representing the flow rate X1 of the metal material added into the container 22 by at least one metal material addition device 30.

[0072] At least one additional sensor 72 is configured to generate data representing at least one additional parameter.

[0073] For example, the at least one additional parameter includes at least one of the following:

[0074] - At least one electrical parameter representing the current flowing through its electrode 38 during EAF 20 operation, a parameter representing arc stability, such as depending on the harmonics of the arc;

[0075] - At least one mechanical parameter representing mechanical waves generated within the vessel during EAF 20 operation. For example, mechanical waves include acoustic waves propagating within the internal volume and vibrations propagating within the walls 26, 27. For example, acoustic waves generated by an electric arc are attenuated by foam slag, which appears with the generation of process gases;

[0076] - The temperature of at least one of the walls 26, 27 and / or the furnace top 28 of the vessel 22, such as the temperature of the cooling system 50, and particularly the temperature of the cooling fluid circulating within the cooling system 50. The process gases are hot, and their generation causes the walls 26, 27 and / or the furnace top 28 of the vessel to warm up;

[0077] - At least one pressure representing the pressure of a process gas, said pressure corresponding to the pressure difference between the internal pressure of container 22 and atmospheric pressure. The generation of the process gas causes an increase in pressure inside container 22;

[0078] - At least one flame parameter representing the flame generated within container 22, including, for example, flame temperature and / or flame size. A flame with high temperature and large size is a hallmark of generating a large volume of process gas. For example, the flame may emerge from the gap between sidewall 27 and removable furnace top 28 and / or the gap between the panel of sidewall 27 and removable furnace top 28; and

[0079] - At least one chemical parameter representing the component properties of the process gas, such as the volume fraction of the process gas component and / or the temperature of the process gas component.

[0080] Advantageously, such as Figure 1 As shown in the example, at least one additional sensor 72 includes at least one of the following:

[0081] - At least one sensor 72A for generating data representing at least one electrical parameter, such as an ammeter, a voltmeter, and / or a Rogowski coil;

[0082] - At least one sensor 72B for generating data representing at least one mechanical parameter, such as a microphone arranged in the internal volume and / or an accelerometer attached to the walls 26, 27;

[0083] - At least one sensor 72C, such as a thermometer, thermocouple, or pyrometer, for generating data representing the temperature of the walls 26, 27 and / or the furnace top 28 of the container 22;

[0084] - At least one sensor 72D for generating data representing the process gas pressure, such as a pressure sensor;

[0085] - At least one sensor 72E for generating data representing at least one flame parameter, such as a thermal imager disposed outside the EAF20 and capable of recording flames emerging from the gap between the sidewall 27 and the removable furnace top 28 and / or the gap between the panels of the sidewall 27 and / or the removable furnace top 28; and

[0086] - At least one sensor 72F for generating data representing at least one chemical parameter, such as a gas analyzer.

[0087] The control module 80 is adapted to receive data representing at least one parameter and is configured to control the suction flow rate Y of the gas suction device 62 based on at least one parameter. For example, the control module 80 controls the suction flow rate Y of the gas suction device 62 by adjusting the suction power of the fan 66 and / or the configuration of valves arranged in the pipe 64.

[0088] Advantageously, during the operation of EAF 20, the control module 80 is configured to adjust the suction flow rate Y of the gas suction device 62 so that the pressure in the internal volume 24 is slightly lower than atmospheric pressure, and in particular, the gas pressure in the container 22 is approximately equal to atmospheric pressure minus 0.15 mBar.

[0089] Also advantageously, the control module 80 is configured to adjust the gas suction flow rate Y of the gas suction device at several adjustment moments during the period of operation of EAF 20.

[0090] Advantageously, the control module 80 is configured to adjust the suction flow rate Y of the gas suction device 62 at each adjustment time based on the value of at least one parameter (e.g., based on the current actual value of at least one parameter at the adjustment time). The control module 80 is configured to derive the value of at least one parameter as a function of data representing at least one parameter received from at least one sensor 70. Advantageously, the control module 80 takes into account the measurement delays of the sensors 70, 72 and the response time of the actuators of the gas suction device 62 (particularly the actuators controlling the fan 66 and / or the valves arranged within the duct 64).

[0091] Also advantageously, the control module 80 is further configured to adjust the suction flow rate Y of the gas suction device 62 at each adjustment time based on the value of at least one additional parameter (e.g., based on the current actual value of at least one additional parameter at the adjustment time).

[0092] For example, the control module 80 is also configured to adjust the suction flow rate Y of the gas suction device 62 at each adjustment time based on a machine learning model that takes into account:

[0093] - During at least a previous run of EAF 20, at least one parameter and / or at least one additional parameter with multiple previous values;

[0094] - The value of the corresponding flow rate Y of the inhaled process gas, which is a function of multiple previous values.

[0095] For example, control module 80 is configured to adjust the suction flow rate Y to be substantially equal to the previous value of at least one parameter and / or at least one additional parameter that corresponds to the current actual value of at least one parameter and / or at least one additional parameter.

[0096] exist Figure 1 In the example shown, the control module 80 is made in the form of software or a software module executable by a processor of an electronic device (not shown). The memory of the electronic device is then able to store the control software. The processor is then able to execute the software.

[0097] In variations not shown, the control module is manufactured as a programmable logic component such as a FPGA (Field Programmable Gate Array) or an integrated circuit such as an ASIC (Application Specific Integrated Circuit).

[0098] When an electronic device is implemented as one or more software programs (i.e., as a computer program, also known as a computer program product), it can also be recorded on a computer-readable medium (not shown). For example, a computer-readable medium is a medium capable of storing electronic instructions and coupled to a bus of a computer system. Examples of such media include optical discs, magneto-optical discs, ROM memory, RAM memory, any type of non-volatile memory (e.g., FLASH or NVRAM), or magnetic cards. The computer program containing the software instructions is stored on the readable medium.

[0099] refer to Figure 2 The present invention describes a method 100 for controlling the extraction of process gases.

[0100] Method 100 is executed at each of the several adjustment times during the time period of EAF 20 operation.

[0101] Advantageously, method 100 includes step 110 of measuring the current actual value of at least one parameter. Specifically, the at least one parameter includes the flow rate X2 of carbonaceous material added into container 22. Advantageously, the carbonaceous material added into the container during EAF 20 operation includes carbonaceous gas added into the container via at least one gas burner 44 and / or at least one carbon gun 46. Advantageously, the at least one parameter also includes the flow rate X1 of metallic material added into container 22 via at least one metallic material adding device 30.

[0102] Advantageously, during step 110, the current actual value of at least one additional parameter is also measured.

[0103] For example, step 110 (particularly the measurement of flow rate X2) is performed by at least one sensor 70, particularly by the carbon-containing material addition sensor 70A, and especially by the first and second sensors 70A1 and 70A2. For example, in step 110, the measurement of the flow rate X1 of the metal material added to the container 22 via at least one metal material addition device 30 is performed by at least one sensor 70B. The flow rate of the carbon-containing material added via at least one metal material addition device 30 is derived based on the flow rate X1 of the added metal material and the carbon content by weight in the added metal material. Advantageously, step 110 (particularly the measurement of the current actual value of at least one additional parameter) is also performed by at least one additional sensor 72.

[0104] During step 110, at least one sensor 70 and optionally at least one sensor 70B generate data representing at least one parameter. For example, the data represents the current actual value of at least one parameter. Advantageously, during step 110, at least one additional sensor 72 generates data representing at least one additional parameter. For example, the data represents the current actual value of at least one additional parameter.

[0105] Advantageously, method 100 further includes step 120 whereby the control module 80 receives data representing at least one parameter and / or representing at least one additional parameter.

[0106] For example, method 100 further includes step 130 of determining the value of at least one parameter and / or at least one additional parameter. In particular, step 130 is performed by control module 80 based on data representing at least one parameter and / or at least one additional parameter received by it from at least one sensor 70 and / or at least one additional sensor 72.

[0107] For example, step 130 includes determining the current actual value of at least one parameter and / or at least one additional parameter at the adjustment time.

[0108] Method 100 further includes step 140 of adjusting the flow rate Y of the intake process gas based on the value of at least one parameter. Advantageously, step 140 is also based on the value of at least one additional parameter. Advantageously, step 140 ensures that during operation of EAF 20, the pressure in internal volume 24 is slightly below atmospheric pressure, specifically ensuring that the gas pressure within internal volume 24 is substantially equal to atmospheric pressure minus 0.15 mBar.

[0109] For example, step 140 is also based on the aforementioned machine learning model.

[0110] For example, if a set of previous values ​​of at least one parameter and / or at least one additional parameter in the model is associated with a specific suction flow rate, and if the current actual value of the corresponding at least one parameter and / or at least one additional parameter corresponds to the set of previous values, then adjustment step 140 is performed such that the suction flow rate is substantially equal to the specific suction flow rate.

[0111] Method 100 further includes step 150 of pumping process gases discharged from container 22 during EAF 20 operation at a pumping flow rate Y adjusted in step 140.

[0112] Advantageously, at least one additional parameter includes at least one of the following:

[0113] - An electrical parameter representing the current flowing through its electrode 38 during EAF 20 operation;

[0114] - Mechanical parameters representing the mechanical waves generated within container 22 during EAF 20 operation;

[0115] - The temperature of the walls 26, 27 and / or the top 28 of the container 22;

[0116] - The pressure representing the process gas pressure, which corresponds to the pressure difference between the internal pressure of container 22 and atmospheric pressure;

[0117] - At least one flame parameter representing the flame generated within container 22, said at least one flame parameter including, for example, flame temperature and / or flame size; and

[0118] - Chemical parameters representing the component properties of process gases.

[0119] Thanks to the invention described in detail above, the process gas extraction flow rate Y is adjusted as a function of the flow rate of the process gas generated within the vessel. Taking into account one or more parameters listed above, particularly accurate extraction flow rate adjustment is possible. This allows for optimal protection of the molten pool from air ingress, while limiting energy consumption for extracting the process gas and restricting leakage of the process gas around vessel 22.

[0120] Furthermore, particularly thanks to the methods described above, the impact of carbon addition on the emitted process gases can be predicted, allowing for proactive control of the extraction of these gases. This is especially true of measuring the flow rates of carbonaceous materials added to the container and / or the flow rates of metallic materials added to the container. This limits the risk of large amounts of air entering the container (in the event of negative pressure within the container) or excessive emissions of process gases and dust around the EAF (in the event of overpressure within the container).

Claims

1. A method (100) for controlling the extraction of process gases emitted from the vessel (22) of an electric arc furnace (20) during operation. The method (100) includes an adjustment step (140) of adjusting the flow rate (Y) of the inhaled process gas based on the value of at least one parameter, the at least one parameter including the flow rate (X2) of carbonaceous material added to the container (22) during operation of the electric arc furnace (20).

2. The method (100) according to claim 1, wherein, The carbonaceous material added to the container (22) during operation of the electric arc furnace (20) includes carbonaceous gas, which is added to the container (22) via a gas burner (44) and / or a carbon gun (46).

3. The method (100) according to claim 1 or 2, wherein, The adjustment step (140) ensures that during operation of the electric arc furnace (20), the gas pressure inside the container (22) is substantially equal to atmospheric pressure minus 0.15 mBar.

4. The method (100) according to any one of the preceding claims, wherein, The method (100) includes a determination step (130) of determining the value of the at least one parameter.

5. The method (100) according to any one of the preceding claims, wherein, The operation of the electric arc furnace (20) takes place over a period of time, and the adjustment step (140) is performed at several adjustment moments within that period of time.

6. The method (100) according to claim 5, wherein, The value of at least one parameter in the adjustment step (140) at each adjustment moment is the current actual value of at least one parameter at that adjustment moment.

7. The method (100) according to claim 6, wherein, The adjustment step (140) is also based on a machine learning model that takes into account: - Multiple previous values ​​of the at least one parameter at a previous adjustment time during at least a previous operation of the electric arc furnace (20); - The value of the corresponding flow rate (Y) of the inhaled process gas as a function of the plurality of previous values.

8. The method (100) according to any one of the preceding claims, wherein, The adjustment step (140) is also based on the value of at least one additional parameter, which includes at least one of the following: - An electrical parameter representing the current flowing through its electrodes (38) during operation of the electric arc furnace (20); - Mechanical parameters representing the mechanical waves generated within the vessel (22) during operation of the electric arc furnace (20); - The temperature of the walls (26, 27) and / or the furnace top (28) of the container (22); - The pressure representing the process gas pressure, which corresponds to the pressure difference between the internal pressure of the container (22) and atmospheric pressure; - At least one flame parameter representing the flame generated within the container (22), the at least one flame parameter including, for example, the temperature and / or size of the flame; as well as - Chemical parameters representing the component properties of process gases.

9. A steel production facility (10), comprising at least: - An electric arc furnace (20) includes a container (22) and at least one means (42) for adding carbonaceous material into the container (22) during operation of the electric arc furnace (20); - Equipment (60) for extracting process gases emitted from its container (22) during operation of the electric arc furnace (20), the equipment (60) comprising: - A device (62) for drawing gas from the container (22); - At least one sensor (70) configured to generate data representing at least one parameter, the at least one parameter including the flow rate (X2) of carbonaceous material added into the container (22). - A control module (80) adapted to receive data representing the at least one parameter and configured to adjust the suction flow rate (Y) of the gas suction device (62) based on the at least one parameter.

10. The steel production facility (10) according to claim 9, wherein, The carbonaceous material added to the container (22) during operation of the electric arc furnace (20) includes carbonaceous gas, and the at least one carbonaceous material adding device (42) includes a gas burner (44) and / or a carbon gun (46).

11. The steel production facility (10) according to claim 9 or 10, wherein, The control module (80) is configured to adjust the suction flow rate (Y) of the gas suction device (62) so that during the operation of the electric arc furnace (20), the gas pressure in the container (22) is substantially equal to atmospheric pressure minus 0.15 mBar.

12. The steel production facility (10) according to any one of claims 9 to 11, wherein, The electric arc furnace (20) is designed to operate within a time period, and the control module (80) is configured to adjust the suction flow rate (Y) of the gas suction device (62) at several adjustment times within that time period.

13. The steel production facility (10) according to claim 12, wherein, The control module (80) is configured to adjust the suction flow rate (Y) of the gas suction device (62) at each adjustment time based on the current actual value of at least one parameter at the adjustment time.

14. The steel production facility (10) according to claim 13, wherein, The control module (80) is configured to adjust the suction flow rate (Y) of the gas suction device (62) at each adjustment time based on a machine learning model, the machine learning model taking into account: - Multiple previous values ​​of the at least one parameter at a previous adjustment time during at least a previous operation of the electric arc furnace (20); - The value of the corresponding flow rate (Y) of the inhaled process gas as a function of the plurality of previous values.

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