Full-process intelligent refining system applied to RH furnace

The intelligent refining system, which integrates multi-module collaborative real-time data acquisition and dynamic adjustment, solves the problems of high alloy material consumption, energy waste, and unstable product quality caused by manual experience and rigid models in the RH furnace refining system. It achieves efficient and precise full-process control, improving steel quality and production efficiency.

CN120989335AActive Publication Date: 2025-11-21HENGYANG RAMON SCI & TECH CO LTD
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Patent Information

Application Number
CN202511524978.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-10-24
Publication Date
2025-11-21
Estimated Expiration
2045-10-24

AI Technical Summary

Technical Problem

Existing RH furnace refining systems rely on manual experience or rigid models, making it difficult to achieve precise and efficient full-process control, resulting in high alloy material consumption, energy waste, and unstable product quality.

Method used

The intelligent refining system employs multi-module collaborative real-time data acquisition and dynamic adjustment, including data acquisition, temperature control, intelligent argon blowing, vacuum control, decarburization control, alloy calculation, and wire feeding control modules. Combined with laser ranging and image recognition technology, it achieves full-process automation and high-precision positioning.

Benefits of technology

It significantly improves the stability of molten steel quality, reduces raw material and energy consumption, reduces safety risks, and improves production efficiency and product consistency.

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Abstract

The invention discloses a full-process intelligent refining system applied to an RH furnace, and belongs to the technical field of ferrous metallurgy. The system comprises a data acquisition module, a temperature control module, an intelligent argon blowing module, a vacuum control module, a decarburization control module, an alloy calculation module, a wire feeding control module and an intelligent control module. The data acquisition module acquires refining data in real time and distributes the refining data to each functional module; the temperature control module calculates the oxygen blowing amount and the aluminum particle adding amount by establishing a molten steel heating model; the intelligent argon blowing module adjusts the argon flow in real time based on image processing; the vacuum control module dynamically maintains a vacuum environment; the decarburization and alloy calculation module accurately calculates the oxygen blowing amount and the alloy adding amount. And the wire feeding control module dynamically sets wire feeding parameters. Through cooperative operation of all the modules, intelligent and accurate control over the whole process from steel ladle entry to steel ladle exit is achieved, and the quality stability of molten steel, the production efficiency and the resource utilization rate are effectively improved.
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Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of steel metallurgy, and particularly relates to a full-process intelligent refining system applied to an RH furnace. BACKGROUND

[0002] The LF furnace is a ladle refining furnace in an atmospheric environment, which can realize steel temperature adjustment, composition fine adjustment and desulfurization by means of electric arc heating and slagging reaction, but is restricted by the atmospheric environment, and has insufficient removal capacity for H, N, O and other gases in the steel, and cannot meet the deep decarburization demand of ultra-low carbon steel.

[0003] The RH furnace (Ruhrstahl-Heraeus furnace, vacuum circulating degassing refining furnace) is a key secondary refining equipment for improving the quality of molten steel in modern steel production, and its main functions include hydrogen removal, oxygen removal, decarburization, inclusion removal and precise adjustment of molten steel composition and temperature. The RH furnace adopts vacuum circulating degassing technology, and the molten steel circulates in the mode of “ascending pipe → vacuum chamber → descending pipe”, which exhibits unique advantages in the vacuum environment: first, the partial pressure of H, N and O in the gas phase can be greatly reduced, and the gases in the steel can be efficiently removed (so that the H in the steel is ≤2 ppm and the N is ≤30 ppm), avoiding defects such as bubbles and lines in the steel; second, the carbon-oxygen reaction is more easily carried out in the vacuum environment, and deep decarburization of ultra-low carbon steel with a carbon content of ≤0.003% can be achieved, which is difficult to achieve in the LF furnace in the atmospheric environment; third, the vacuum environment reduces the burning loss of Al, Ti and other easily oxidized alloy elements, improving the alloy recovery rate and composition control accuracy; fourth, the circulating flow makes the composition and temperature of the molten steel more uniform, ensuring the quality stability of batch products. In summary, the RH furnace has significant advantages in refining ultra-low carbon and high-purity steel, and can fundamentally improve the density, toughness and fatigue strength of steel, meeting the stringent requirements of high-end fields for steel performance. The effect of the RH refining process directly determines the quality and performance of the final steel product.

[0004] At present, the refining control technology applied to the RH furnace mainly includes the following two types: Manual experience-based operation mode: in this mode, the operator adjusts the process parameters by observing the instrument readings and his own experience, which is flexible but has poor stability. The judgment difference between different operators will cause the refining effect to fluctuate, the product quality is difficult to keep consistent, and the production efficiency is also low.

[0005] Fixed parameter model-based automation control technology: this technology reduces manual intervention to some extent and improves operation efficiency, but it is essentially a "preset" control. The system cannot dynamically adjust according to the actual state of the molten steel (such as real-time changes in composition, temperature), and it is not adaptable to the refining needs of different heats and different steel grades. This often leads to high alloy consumption, energy waste, and even product quality problems due to insufficient control accuracy.

[0006] Overall, existing technologies either rely too much on human experience and lack stability, or are rigid in model and lack adaptability, making it difficult to achieve precise, efficient, and full-process optimization control. Therefore, there is an urgent need for an RH refining system that can intelligently respond to changes in molten steel state and achieve precise control throughout the process to overcome the shortcomings of existing technologies. SUMMARY

[0007] To solve the above problems, the present application provides a full-process intelligent refining system applied to an RH furnace, which aims to realize precise and intelligent control of the RH furnace refining process by real-time data collection and dynamic adjustment of process parameters through multi-module cooperation, thereby improving the stability of molten steel quality and production efficiency.

[0008] The present application provides a full-process intelligent refining system applied to an RH furnace, comprising the following modules: A data acquisition module for real-time acquisition of refining-related data in the furnace, and sending the acquired data to a temperature control module, an intelligent argon blowing module, a vacuum control module, a decarburization control module, an alloy calculation module, and a wire feeding control module as needed; A temperature control module based on real-time acquisition of molten steel temperature data and molten steel process information to establish a molten steel temperature rise model and calculate the oxygen blowing amount and aluminum particle addition amount to control the molten steel temperature; An intelligent argon blowing module for processing and analyzing images of the ladle liquid surface to adjust the argon flow rate in real time; A vacuum control module for adjusting the running state of the vacuum pump based on the collected vacuum degree in the furnace, and compensating according to the collected vacuum pipeline leakage; A decarburization control module for calculating the oxygen blowing amount required for decarburization according to the carbon content of the molten steel, and regulating the molten steel decarburization reaction process according to the oxygen blowing amount; An alloy calculation module for establishing an alloy model to calculate the alloy addition amount based on the target value of the molten steel composition and the yield; A wire feeding control module for dynamically setting the wire feeding speed, length, and timing according to the refining needs of the molten steel; An intelligent control module for generating control instructions to control system operation.

[0009] Further, the system further comprises: The ladle car control module is used for collecting the distance parameter of the ladle car and the predicted marker in real time by using a laser range finder, synchronously analyzing the surrounding environment information by using an image processing algorithm, and realizing the positioning and intelligent walking control of the ladle car. The ladle control module is used for adjusting the operation of the jacking mechanism to control the lifting height of the ladle according to the refining process requirements.

[0010] The whole process automation and high-precision positioning of the ladle transportation and lifting are realized, the obstacles are effectively avoided through the fusion technology of laser ranging and image recognition, the operation safety is ensured, the foundation guarantee is provided for the continuous and stable operation of the refining process, and the positioning errors and safety accidents caused by manual operation are reduced.

[0011] Further, the data acquisition module acquires data through an industrial robot, the robot is equipped with a temperature sensor and a sampling device, and the data acquisition operation is performed through multi-degree-of-freedom movement of the mechanical arm.

[0012] The industrial robot is used to replace manual operation, automatic temperature measurement and sampling in a high-temperature and high-risk environment are realized, the precision and efficiency of data acquisition are greatly improved, the personnel safety is greatly guaranteed, and subjective errors and safety risks caused by manual operation are avoided.

[0013] Further, the operation process of the temperature control module includes the following steps: obtaining real-time temperature data of the molten steel; When the temperature is in the preset temperature interval, the difference between the target temperature and the real-time temperature is calculated, and the aluminum particles and the oxygen blowing amount required to be added are calculated according to the difference; The total value of the oxygen content of the molten steel and the residual oxygen content of the vacuum chamber is calculated, when the total value is greater than the required oxygen blowing amount, the decarburization control module updates the residual oxygen content of the molten steel as the difference between the total value and the oxygen blowing amount, and outputs the aluminum particle addition amount and the residual oxygen content of the molten steel; When the total value is less than or equal to the required oxygen blowing amount, the decarburization control module updates the residual oxygen content of the molten steel to 0, and outputs the aluminum particle addition amount and the oxygen blowing amount.

[0014] By calculating the total oxygen content in the molten steel and the vacuum chamber and comparing it with the demand, intelligent allocation and collaborative use of oxygen resources are realized, which not only ensures the accurate control of the aluminum thermal heating reaction, but also reserves oxygen resources for subsequent decarburization reaction, reduces oxygen waste, and optimizes the overall reaction efficiency.

[0015] Further, the aluminum particles and the oxygen blowing amount required to be added according to the difference are calculated by using the following formula: ; ; Among them, indicates the aluminum particles required for the molten steel to be heated up; Indicates the target temperature for heating; Indicates the measured temperature at the destination station; s represents the temperature at which 1 kg of aluminum granules react completely with the molten steel. This indicates the amount of oxygen required for the steel to heat up and react. This represents the ratio of theoretical oxygen mass to aluminum particle mass. Indicates oxygen density; It represents the ratio of the amount of oxygen entering the molten steel to participate in the reaction to the total amount of oxygen blown in.

[0016] Based on the aluminothermic reaction mechanism, a precise mathematical model was established, enabling quantitative and accurate calculation of oxygen blowing volume and aluminum particle addition. This overcomes the blindness of traditional experience-based control, significantly improves the accuracy and stability of temperature control, and reduces alloy and energy consumption.

[0017] Furthermore, the intelligent argon blowing module specifically includes: The image processing unit is used to acquire and process images of the liquid surface in the ladle in real time; The data processing unit is used to analyze and calculate the data acquired by the image processing unit to determine the adjustment direction of the argon flow rate; The argon gas regulating unit automatically adjusts the argon gas flow rate according to the direction of argon gas flow adjustment. The system alarm unit issues an alarm in abnormal situations to ensure the safe operation of the system.

[0018] By analyzing the boiling state of the liquid surface in real time through machine vision and intelligently adjusting the argon flow rate, the closed-loop precise control of the argon blowing process is achieved, which can not only ensure excellent stirring effect, but also effectively prevent splashing. The built-in abnormal handling mechanism ensures that the system can still operate safely and reliably when the camera is blocked or malfunctions, demonstrating a high level of intelligence.

[0019] Furthermore, the calculation of the oxygen blowing amount required for decarburization based on the carbon content of the molten steel specifically includes: Calculate the total amount of decarburization required based on the initial carbon content and the target carbon content of the molten steel. According to the decarbonization reaction equation The ratio of the theoretical oxygen mass to the carbon mass is obtained; Calculate the required oxygen blowing amount for decarbonization based on the total amount of carbon to be removed and the ratio of theoretical oxygen mass to carbon mass: ; in, This indicates the amount of oxygen required for decarbonization; M represents the quality of molten steel; represents the total amount of decarburization required; represents the ratio of the mass of oxygen to the mass of carbon.

[0020] The oxygen blowing amount required is accurately calculated based on the decarburization reaction principle, realizing the transition of the decarburization process from empirical judgment to quantitative control, effectively avoiding the problems of oxygen excess or deficiency, thereby reducing oxygen consumption while ensuring decarburization efficiency and improving the hit rate of the final carbon content.

[0021] Further, the alloy calculation module establishes an alloy model as follows: ; wherein, is the addition amount of the i-th alloy; represents the initial content of the required alloying element in the molten steel; represents the final content of the required alloying element in the molten steel; represents the yield of the required element in the i-th alloy; represents the mass fraction of the required element in the i-th alloy.

[0022] By introducing key parameters such as yield and element content, a mathematical model is established to accurately calculate the alloy addition amount, significantly improving the yield of alloying elements and the precision of composition control, reducing the waste of alloy materials, and stabilizing the molten steel quality.

[0023] Further, the wire feeding control module calculates the wire feeding length by the following formula: L=(A×M) / (B×X); wherein, L is the length of calcium wire to be fed; A is the target calcium content of the molten steel; B is the calcium wire yield; X is the mass of calcium per meter of calcium wire.

[0024] The wire feeding operation is changed from empirical estimation to precise calculation driven by process targets and mathematical models, which can accurately determine the wire feeding length according to the molten steel quality and target calcium content, thereby effectively avoiding the problems of calcium wire waste or poor calcium treatment effect while achieving the target of inclusion modification or composition fine-tuning.

[0025] Further, the specific refining process of the whole-process intelligent refining system is as follows: Start intelligent refining - automatically collect steel grade process data - ladle in place - ladle lifting - temperature measurement, sampling, oxygen determination - calculate aluminum oxygen heating - side argon blowing regulation - pre-vacuum - oxygen blowing decarburization - vacuum holding - alloy ratio - breaking empty - temperature measurement, sampling - ladle reset - bottom argon blowing regulation - automatic wire feeding - soft blowing end closing argon - production performance automatic uploading - ladle outbound.

[0026] A complete and coherent full-process automatic refining process is defined, realizing unmanned intelligent collaborative operation of all core processes from ladle inbound to outbound, greatly improving production efficiency and consistency of process execution, reducing human intervention, and being a concentrated embodiment of the overall intelligent advantage of the system.

[0027] Compared with the prior art, the beneficial effects of the present application are: the present application realizes precise matching and collaborative operation of each link parameter by accurately controlling aluminum thermal reaction to heat the molten steel, and combining with real-time data intelligent decarburization, alloying, wire feeding, etc., significantly improves the stability of molten steel quality, reduces raw material and energy consumption, reduces safety risks and pollutant emissions, and at the same time relies on automation and intelligent control to improve production efficiency, optimize production management, and comprehensively enhance the comprehensive benefits and competitiveness of the steelmaking process. BRIEF DESCRIPTION OF DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the drawings, and other drawings can be obtained by those skilled in the art without creative labor based on the structures shown in the drawings.

[0029] Figure 1 The structural schematic diagram of the present application. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical scheme and advantages of the present application more clear, the present application will be described and explained in the following with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application. Based on the embodiments provided by the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application.

[0031] The present application provides a full-process intelligent refining system applied to an RH furnace, as shown in Figure 1 The specific modules include: A data acquisition module is configured to acquire real-time refining data in a furnace, and send the acquired data to a temperature control module, an intelligent argon blowing module, a vacuum control module, a decarburization control module, an alloy calculation module, and a wire feeding control module.

[0032] The data acquisition module acquires data through an industrial robot, which is equipped with a temperature sensor and a sampling device, and performs data acquisition operation through multi-degree-of-freedom movement of a mechanical arm, and stores the acquired data into a business database.

[0033] The temperature control module establishes a molten steel temperature rising model through an algorithm based on real-time acquired molten steel temperature data and molten steel process information, and calculates oxygen blowing amount and aluminum particle adding amount to control molten steel temperature.

[0034] The operation process of the temperature control module includes the following steps: acquiring real-time molten steel temperature data; when the temperature is in a preset temperature range, calculating a difference between a target temperature and a real-time temperature, calculating aluminum particles and oxygen blowing amount to be added according to the difference, and calculating by using the following formula: ; ; wherein, represents aluminum particles required for molten steel temperature rising; represents a target temperature of temperature rising; represents a measured temperature at a station; s represents a temperature rising of 1 kg of aluminum particles; represents oxygen blowing amount required for molten steel temperature rising reaction; represents a theoretical oxygen mass to aluminum particle mass ratio; represents oxygen density; represents a ratio of oxygen amount entering molten steel for reaction to total oxygen blowing amount.

[0035] Specifically, the aluminum thermal reaction equation is: ; It can be known that 2 moles of Al consume 3 moles of O, and thus the theoretical oxygen mass to aluminum particle mass ratio is: ; Therefore, the theoretical oxygen requirement amount of the aluminum thermal reaction In the actual oxygen blowing process, not all of the oxygen blown from the oxygen blowing equipment can enter the molten steel to participate in the reaction, and part of the oxygen can be retained in the furnace gas without actually entering the molten steel. For example, if the total oxygen blowing amount is 1000 m3, and the oxygen blowing rate is 100 m3 / min, the oxygen blowing time is 10 min. However, not all of the oxygen blown can enter the molten steel to participate in the reaction, and part of the oxygen can be retained in the furnace gas without actually entering the molten steel. For example, if the total oxygen blowing amount is 1000 m3, and the oxygen blowing rate is 100 m3 / min, the oxygen blowing time is 10 min. , wherein the amount of oxygen entering the molten steel to participate in the reaction is , then . By introducing , the amount of oxygen actually required to be blown in can be calculated using the formula

[0036] The following formula is used to calculate the oxygen content in the molten steel actually blown in by oxygen : ; , wherein the oxygen density ; V represents the volume of oxygen blowing; M represents the mass of the molten steel; When the mass of the molten steel is 130 t, , and the oxygen blowing rate is 100 m3 / min, the oxygen content in the molten steel calculated by blowing in 1 m3of oxygen is: 3 .

[0037] The total value of the oxygen content in the molten steel and the residual oxygen amount in the vacuum chamber is calculated. When the total value is greater than the required oxygen blowing amount, the decarburization control module updates the residual oxygen content in the molten steel as the difference between the total value and the oxygen blowing amount, and outputs the aluminum particle addition amount and the residual oxygen content in the molten steel; When the total value is less than or equal to the required oxygen blowing amount, the decarburization control module updates the residual oxygen content in the molten steel to 0, and outputs the aluminum particle addition amount and the oxygen blowing amount.

[0038] The intelligent argon blowing module is used to process and analyze the image of the liquid surface of the ladle to adjust the argon flow in real time.

[0039] Specifically, the intelligent argon blowing module includes the following units: The image processing unit is used to acquire and process the image of the liquid surface of the ladle in real time.

[0040] The coverage range of side blowing and stirring is analyzed by contour segmentation and region statistics method. After the camera is installed, the system sets ROI (region of interest) in the specified area of the side wall, dynamically calculates the coverage rate of the liquid surface stirring in real time, and sets the corresponding coverage rate standard range (the actual standard can be adjusted according to the specific process requirements) for different process stages, for example, the normal smelting process requires a coverage rate of ≥60%, and the decarburization stage requires a coverage rate of ≥85%.

[0041] The data processing unit is used to analyze and calculate the data obtained by the image processing unit to determine the adjustment direction of the argon flow.

[0042] ​​The unit automatically increases the flow of argon according to the real-time feedback of the coverage data when the current coverage is lower than the process set standard. To prevent overshooting, the system sets an adjustable range for the argon flow under each process state, for example, the flow adjustment range for the vacuum stage is set to 60-100 Nm 3 / h (the specific range can be set according to the requirements of the equipment and process).

[0043] The argon regulation unit automatically adjusts the argon flow according to the adjustment direction of the argon flow.

[0044] The system alarm unit issues an alarm in abnormal situations to ensure the safe operation of the system, including the following two abnormal processing mechanisms: Image detection blind area processing: If the image recognition coverage does not meet the standard due to dust obstruction, but other process parameters are normal, an alarm is triggered to clean the camera, and after the image is clear, the flow adjustment is performed to avoid misoperation.

[0045] Emergency adjustment logic: When image detection fails (such as camera offline), the system automatically switches to "pure process parameter adjustment mode" and fine-tunes the side blowing flow within the range of ±10% of the basic value, while issuing a warning signal to prompt the staff to check the image equipment.

[0046] The vacuum control module adjusts the running state of the vacuum pump based on the collected vacuum degree in the furnace, and compensates according to the collected vacuum pipeline leakage.

[0047] This module continuously monitors the system pressure through high-precision vacuum degree sensors and uses intelligent control algorithms (such as fuzzy control) to dynamically adjust the working parameters of the vacuum pump. At the same time, the system can monitor whether there is a leak in the vacuum pipeline, and based on the pressure change, it realizes rapid compensation, thereby providing continuous and stable vacuum conditions for metallurgical reactions such as degassing and decarburization, effectively improving the purity of molten steel.

[0048] The start-stop control of the vacuum pump follows a hierarchical operation logic, referring to the following process (the actual pressure set value can be adjusted according to the working condition): 1. When starting to vacuum, start the 5a level pump; 2. When the vacuum degree reaches 80 kPa, start the 5b level pump; 3. When reaching 40 kPa, start the 4a level pump; 4. When reaching 30 kPa, start the 4b level pump; 5. When reaching 8 kPa, start the s3 level pump; 6. When reaching 2.5 kPa, start the s2 level pump; 7. When reaching 0.5 kPa, start the s1 level pump.

[0049] The sealing performance of the vacuum pipeline is crucial to the stability of the system. This module ensures the vacuum environment through the "feature recognition - hierarchical compensation - emergency treatment" mechanism, which specifically includes: Leakage feature recognition: Monitor the slope change of the vacuum-time curve. Under normal working conditions, the vacuum decreases with time, and the curve slope is negative and gradually flattens. If a leak occurs, the absolute value of the slope will abnormally decrease or even become positive.

[0050] Monitor the data of the pipeline pressure sensor. The pressure near the leakage point will abnormally rise due to air infiltration.

[0051] The system integrates the above information to determine the leakage location and severity in real time, such as distinguishing between minor and serious leaks.

[0052] Compensation and emergency treatment strategy: Minor leak (vacuum drop rate < P1 Pa / min, P1 value adjusted according to the site): The control algorithm automatically increases the vacuum pump pumping capacity to compensate for the vacuum loss caused by the leak, maintaining the stability of the vacuum environment; Serious leak (vacuum drop rate ≥ P2 Pa / min, P2 value adjusted according to the site): The system triggers an audible and visual alarm and initiates emergency operations, such as closing the isolation valve near the leak area (if the pipeline is segmented), and simultaneously increasing the vacuum pump pumping speed to the maximum to maintain system safety.

[0053] Decarburization control module, used to calculate the oxygen blowing amount required for decarburization according to the carbon content of the molten steel, and to regulate the decarburization reaction process according to the oxygen blowing amount.

[0054] This module accurately calculates the required oxygen blowing amount through the decarburization model, and adjusts the decarburization reaction process and conditions accordingly to achieve efficient and accurate decarburization, ultimately achieving the target carbon content of the molten steel.

[0055] The decarburization amount is calculated as follows: ; Where, represents the total amount of decarburization required; represents the initial carbon content of the molten steel; represents the target carbon content of the molten steel; represents the carbon increment after adding alloy to the molten steel.

[0056] The decarburization reaction equation is: ; From the above decarburization reaction equation, it can be seen that 1 mole of C consumes 1 mole of O, therefore, the theoretical oxygen mass With carbon mass Ratio Is: .

[0057] According to the total amount of decarburization required and the ratio of theoretical oxygen mass to carbon mass, the oxygen blowing amount required for decarburization is calculated : .

[0058] An alloy calculation module is used to establish an alloy model according to the target value of molten steel composition and the yield to calculate the alloy addition amount.

[0059] Specifically, according to the initial composition of molten steel and the target composition requirement, the type and quantity of alloy addition are accurately calculated, the precise addition of alloy is realized, and it is ensured that the composition of molten steel meets the production standard. The yield of alloy in the RH furnace is relatively stable, and the amount of alloy addition can be accurately calculated by establishing a mathematical model based on mechanism, and then accurately added by the alloy weighing and adding system, and adjusted according to the real-time monitoring data of composition. The alloy model established according to the yield and the target value of alloy elements is as follows: ; Among them, is the amount of the i-th alloy added; represents the initial content of the required alloy element in the molten steel; represents the final content of the required alloy element in the molten steel; represents the yield of the required element in the i-th alloy; represents the mass fraction of the required element in the i-th alloy.

[0060] A wire feeding control module is used to dynamically set the wire feeding speed, length and timing according to the refining requirements of molten steel.

[0061] Specifically, according to the refining requirements of molten steel, the wire feeding speed, length and timing of the wire feeder are intelligently controlled, the functional wire (such as calcium wire) is accurately and uniformly fed into the molten steel, and the quality of the molten steel is improved. Combined with real-time data such as molten steel composition, temperature, etc., the algorithm is used to determine the wire feeding parameters, the wire feeder executes the operation through the high-precision speed and length control device (encoder), and the position monitoring device feedbacks the wire feeding state, ensuring the process to be accurate and continuous.

[0062] The essence of calcium feeding operation is to provide sufficient calcium elements to the molten steel through calcium wire to meet the modification of inclusions (such as Al2O3→12CaO 7Al2O3) or steel composition fine-tuning requirements. For inclusion modification, the required wire feeding length can be classified according to the steel grade, and a standard wire feeding amount database is established for query. For composition fine-tuning, the basic calculation formula of the wire feeding length is: L = (A x m) / (B x X); L is the length of calcium wire to be fed (m); A is the target calcium content of the molten steel (%); M is the mass of the molten steel (kg); B is the calcium wire recovery rate (%); X is the mass of calcium in each meter of calcium wire (kg / m).

[0063] The intelligent control module generates control instructions based on all other modules to control the system operation.

[0064] The ladle car control module is used to collect the distance parameters of the ladle car and the predicted markers in real time using a laser range finder, and simultaneously analyze the surrounding environment information using an image processing algorithm to realize the positioning and intelligent walking control of the ladle car.

[0065] Specifically, this module uses laser positioning technology, integrates real-time detection of a laser range finder and image processing auxiliary judgment, realizes high-precision positioning and intelligent walking control of the ladle car. The laser range finder collects the distance parameters of the ladle car and the preset markers in real time, and simultaneously analyzes the surrounding environment information such as track obstacles using image processing algorithms (such as YOLOv5, Faster R-CNN). The system dynamically adjusts the driving system by fusing multiple data sources to ensure the positioning accuracy and safe driving of the ladle car, and avoids the impact of position deviation on the refining process, providing a stable foundation for the subsequent process.

[0066] The ladle control module is used to adjust the operation of the lifting mechanism to control the lifting height of the ladle according to the refining process requirements.

[0067] Specifically, this module uses a hydraulic or electric lifting mechanism as a power source, and a displacement sensor is used to monitor the lifting height of the ladle in real time. The control system adjusts the operation of the lifting mechanism according to the refining process requirements to realize stable and accurate lifting of the ladle.

[0068] Further, the specific refining process of the full-process intelligent refining system is as follows: Start intelligent refining - automatically collect steel process data - ladle in place - ladle lifting - temperature measurement, sampling, oxygen determination - calculate aluminum oxygen heating - side argon blowing regulation - pre-vacuum - oxygen blowing decarburization - vacuum holding - alloy proportioning - breaking vacuum - temperature measurement, sampling - ladle reset - bottom argon blowing regulation - automatic wire feeding - soft blowing end closing argon - production performance automatic uploading - ladle outbound.

[0069] Note that the present application is not limited to the above-described embodiments. The above-described embodiments are merely examples, and embodiments having substantially the same configuration as the technical idea and achieving the same effects within the scope of the technical idea of the present application are included in the technical scope of the present application. Furthermore, other modes constructed by applying various modifications that can be thought of by those skilled in the art to the embodiments or by combining part of the constituent elements of the embodiments are also included in the scope of the present application without departing from the spirit of the present application.

Claims

1. A fully intelligent refining system for an RH furnace, characterized in that, include: The data acquisition module is used to collect relevant data on refining in the furnace in real time; The temperature control module establishes a molten steel temperature rise model based on real-time collected molten steel temperature data and molten steel process information, and calculates the oxygen blowing amount and aluminum particle addition amount to control the molten steel temperature. The intelligent argon blowing module is used to process and analyze images of the liquid surface in the ladle to adjust the argon flow rate in real time. The vacuum control module adjusts the operation of the vacuum pump based on the collected vacuum level inside the furnace, and compensates for leaks in the vacuum pipeline based on the collected data. The decarburization control module is used to calculate the amount of oxygen required for decarburization based on the carbon content of the molten steel, and to regulate the decarburization reaction process of the molten steel according to the amount of oxygen blown. The alloy calculation module is used to establish an alloy model based on the target value of molten steel composition and yield to calculate the amount of alloy to be added. The wire feeding control module is used to dynamically set the wire feeding speed, length, and timing according to the steel refining requirements; The intelligent control module is used to generate control commands to control the system's operation.

2. The fully intelligent refining system applied to an RH furnace as described in claim 1, characterized in that, The system also includes: The ladle car control module is used to collect the distance parameters between the ladle car and the predicted markers in real time using a laser rangefinder, and simultaneously use image processing algorithms to analyze the surrounding environment information to realize the positioning and intelligent walking control of the ladle car; The ladle control module is used to adjust the operation of the lifting mechanism to control the lifting height of the ladle according to the refining process requirements.

3. The fully intelligent refining system applied to an RH furnace as described in claim 1, characterized in that, The data acquisition module collects data through an industrial robot. The robot is equipped with a temperature sensor and a sampling device, and performs data acquisition operations through the multi-degree-of-freedom movement of the robotic arm.

4. The fully intelligent refining system applied to an RH furnace as described in claim 1, characterized in that, The operation of the temperature control module includes the following steps: Obtain real-time temperature data of molten steel; When the temperature is within the preset temperature range, calculate the difference between the target temperature and the real-time temperature, and calculate the amount of aluminum particles and oxygen to be added based on the difference; The total value of the oxygen content in molten steel and the residual oxygen content in the vacuum chamber is calculated. When the total value is greater than the required oxygen blowing amount, the decarburization control module updates the residual oxygen content in molten steel to the difference between the total value and the oxygen blowing amount, and outputs the amount of aluminum particles added and the residual oxygen content in molten steel. When the total value is less than or equal to the required oxygen blowing amount, the decarburization control module updates the remaining oxygen content of the molten steel to 0 and outputs the amount of aluminum particles added and the amount of oxygen blowing.

5. The fully intelligent refining system for an RH furnace as described in claim 4, characterized in that, The calculation of the required aluminum granules and oxygen blowing amount based on the difference is specifically performed using the following formula: ; ; in, This indicates the amount of aluminum granules required to heat the molten steel. Indicates the target temperature for heating; Indicates the measured temperature at the destination station; s represents the temperature at which 1 kg of aluminum granules react completely with the molten steel. This indicates the amount of oxygen required for the steel to heat up and react. This represents the ratio of theoretical oxygen mass to aluminum particle mass. Indicates oxygen density; It represents the ratio of the amount of oxygen entering the molten steel to participate in the reaction to the total amount of oxygen blown in.

6. The fully intelligent refining system applied to an RH furnace as described in claim 1, characterized in that, The intelligent argon blowing module specifically includes: The image processing unit is used to acquire and process images of the liquid surface in the ladle in real time; The data processing unit is used to analyze and calculate the data acquired by the image processing unit to determine the adjustment direction of the argon flow rate; The argon gas regulating unit automatically adjusts the argon gas flow rate according to the direction of argon gas flow adjustment. The system alarm unit issues an alarm in abnormal situations to ensure the safe operation of the system.

7. The fully intelligent refining system applied to an RH furnace as described in claim 1, characterized in that, The calculation of the oxygen blowing amount required for decarburization based on the carbon content of the molten steel specifically includes: Calculate the total amount of decarburization required based on the initial carbon content and the target carbon content of the molten steel. According to the decarbonization reaction equation The ratio of the theoretical oxygen mass to the carbon mass is obtained; Calculate the required oxygen blowing amount for decarbonization based on the total amount of carbon to be removed and the ratio of theoretical oxygen mass to carbon mass: ; in, This indicates the amount of oxygen required for decarbonization; M represents the quality of molten steel; Indicates the total amount of carbon removal required; This represents the ratio of the theoretical oxygen mass to the carbon mass.

8. The fully intelligent refining system applied to an RH furnace as described in claim 1, characterized in that, The alloy model established by the alloy calculation module is as follows: ; in, The amount of the i-th alloy added; This indicates the initial content of the alloying elements required in the molten steel; This indicates the final content of alloying elements required in the molten steel; This represents the yield of the desired element in the i-th alloy; This represents the mass fraction of the required element in the i-th alloy.

9. The fully intelligent refining system applied to an RH furnace as described in claim 1, characterized in that, The wire feeding control module calculates the wire feeding length using the following formula: L = (A × M) / (B × X); Where L is the length of the calcium wire to be fed in; A represents the target calcium content in the molten steel; B represents the calcium line yield; X represents the mass of calcium per meter of calcium line.

10. The fully intelligent refining system applied to an RH furnace as described in claim 1, characterized in that, The specific refining process of the fully intelligent refining system is as follows: Start intelligent refining - automatically collect steel grade process data - ladle in place - ladle lifting - temperature measurement, sampling, oxygen determination - calculate aluminum-oxygen temperature rise - side blowing argon gas adjustment - pre-vacuuming - oxygen blowing for decarburization - vacuum maintenance - alloy proportioning - venting - temperature measurement, sampling - ladle reset - bottom blowing argon gas adjustment - automatic wire feeding - soft blowing ends and argon gas shut off - production data automatically uploaded - ladle leaving the station.

Citation Information

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