A full-process intelligent refining system applied to RH furnace

Abstract

The application discloses a full-process intelligent refining system applied to an RH furnace and belonging to the technical field of steel metallurgy. The system comprises data acquisition, temperature control, intelligent argon blowing, vacuum control, decarburization control, alloy calculation, wire feeding control and intelligent control modules. The data acquisition module acquires refining data in real time and distributes the data to various functional modules; the temperature control module calculates oxygen blowing quantity and aluminum particle adding quantity by establishing a molten steel temperature rising model; the intelligent argon blowing module adjusts argon flow in real time based on image processing; the vacuum control module dynamically maintains a vacuum environment; the decarburization and alloy calculation modules accurately calculate oxygen blowing quantity and alloy adding quantity respectively; and the wire feeding control module dynamically sets wire feeding parameters. Through the collaborative work of various modules, the application realizes full-process intelligent and accurate control from ladle entry to exit, and effectively improves molten steel quality stability, production efficiency and resource utilization.

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 liquid 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 accurate 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 carbon content ≤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 yield 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:

[0005] 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.

[0006] 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.

[0007] In general, 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

[0008] 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.

[0009] The present application provides a full-process intelligent refining system applied to an RH furnace, comprising the following modules:

[0010] A data acquisition module for real-time acquisition of refining-related data in the furnace, and sending the acquired data to the temperature control module, intelligent argon blowing module, vacuum control module, decarburization control module, alloy calculation module, and wire feeding control module as needed;

[0011] 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;

[0012] An intelligent argon blowing module for processing and analyzing images of the ladle liquid surface to adjust the argon flow rate in real time;

[0013] 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;

[0014] 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;

[0015] An alloy calculation module for establishing an alloy model based on the target value of the molten steel composition and the yield to calculate the alloy addition amount;

[0016] A wire feeding control module for dynamically setting the wire feeding speed, length, and timing according to the refining needs of the molten steel.

[0017] The intelligent control module is configured to generate control instructions to control the system to operate.

[0018] Further, the system further comprises:

[0019] The ladle car control module is configured to collect distance parameters between the ladle car and the predicted markers in real time by using a laser range finder, and to analyze surrounding environment information by using an image processing algorithm synchronously, so as to realize positioning and intelligent walking control of the ladle car.

[0020] The ladle control module is configured to adjust the operation of the lifting mechanism to control the lifting height of the ladle according to the requirements of the refining process.

[0021] The system realizes full automation and high-precision positioning of the transportation and lifting of the ladle, effectively avoids obstacles through the fusion of laser ranging and image recognition technology, ensures operation safety, provides basic support for the continuous and stable operation of the refining process, and reduces positioning errors and safety accidents caused by manual operation.

[0022] Further, the data acquisition module acquires data by using an industrial robot, the robot is equipped with a temperature sensor and a sampling device, and data acquisition operations are performed through multi-degree-of-freedom movement of the mechanical arm.

[0023] The industrial robot is used to replace manual operation, which realizes automatic temperature measurement and sampling in a high-temperature and high-risk environment, greatly improves the accuracy and efficiency of data acquisition, and greatly ensures personnel safety, avoiding subjective errors and safety risks caused by manual operation.

[0024] Further, the operation process of the temperature control module includes the following steps:

[0025] Obtain real-time temperature data of the molten steel;

[0026] 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 the amount of oxygen to be added according to the difference;

[0027] Calculate the total value of the oxygen content of the molten steel and the residual oxygen content of the vacuum chamber, and 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 amount of aluminum particles to be added and the residual oxygen content of the molten steel.

[0028] 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 amount of aluminum particles to be added and the oxygen blowing amount.

[0029] 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 precise control of the aluminum hot heating reaction, but also reserves oxygen resources for the subsequent decarburization reaction, reduces oxygen waste, and optimizes the overall reaction efficiency.

[0030] Further, the aluminum particles and the oxygen blowing amount to be added are calculated according to the difference value, specifically by using the following formula:

[0031] ;

[0032] ;

[0033] Among them, indicates the aluminum particles required for the molten steel to be heated up;

[0034] indicates the target temperature of heating up;

[0035] indicates the measured temperature at the station;

[0036] s indicates the heating temperature of 1 kg of aluminum particles for the molten steel;

[0037] indicates the oxygen blowing amount required for the molten steel heating reaction;

[0038] indicates the theoretical oxygen mass to aluminum particle mass ratio;

[0039] indicates the oxygen density;

[0040] indicates the ratio of the oxygen amount entering the molten steel for reaction to the total oxygen blowing amount.

[0041] Based on the aluminum hot reaction mechanism, an accurate mathematical model is established to realize quantitative and precise calculation of the oxygen blowing amount and the aluminum particle addition amount, overcome the blindness of traditional experience control, significantly improve the precision and stability of temperature control, and reduce alloy and energy consumption.

[0042] Further, the intelligent argon blowing module specifically includes:

[0043] An image processing unit for real-time acquisition and processing of the image of the ladle liquid level;

[0044] A data processing unit for analyzing and calculating the data acquired by the image processing unit to determine the adjustment direction of the argon flow;

[0045] An argon regulating unit for automatically adjusting the argon flow according to the adjustment direction of the argon flow;

[0046] System alarm unit, in abnormal circumstances, send out an alarm, to ensure the safe operation of the system.

[0047] Through real-time analysis of liquid surface boiling state by machine vision and intelligent adjustment of argon flow, closed-loop precise control of argon blowing process is realized, 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 run safely and reliably when the camera is blocked or fails, and the intelligent level is high.

[0048] Further, the oxygen blowing amount required for decarburization according to the carbon content of molten steel specifically includes:

[0049] According to the initial carbon content of molten steel and the target carbon content of molten steel, the total amount of decarburization required is calculated;

[0050] According to the decarburization reaction equation The ratio of theoretical oxygen mass to carbon mass is obtained;

[0051] 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:

[0052] ;

[0053] Wherein, The oxygen blowing amount required for decarburization is represented by M;

[0054] M represents the mass of molten steel;

[0055] The total amount of decarburization required is represented by M;

[0056] The ratio of theoretical oxygen mass to carbon mass is represented by M.

[0057] Based on the principle of decarburization reaction, the required oxygen blowing amount is accurately calculated, realizing the transition from empirical judgment to quantitative control in the decarburization process, effectively avoiding the problem of excessive or insufficient oxygen, thereby ensuring the decarburization efficiency while reducing oxygen consumption, and improving the hit rate of end carbon content.

[0058] Further, the alloy calculation module establishes an alloy model as follows:

[0059] ;

[0060] Wherein, The amount of the i-th alloy added is represented by M;

[0061] The initial content of the required alloy element in molten steel is represented by M;

[0062] The final content of the required alloy element in molten steel is represented by M.

[0063] Yi represents the yield of the required element in the i-th alloy;

[0064] Xi represents the mass fraction of the required element in the i-th alloy.

[0065] By introducing key parameters such as yield and element content, a mathematical model is established to realize accurate calculation of alloy addition amount, significantly improve the accuracy of yield and composition control of alloy elements, reduce the waste of alloy materials, and stabilize the quality of molten steel.

[0066] Further, the wire feeding control module calculates the wire feeding length by the following formula:

[0067] L=(A×M) / (B×X);

[0068] Wherein, L is the length of calcium wire to be fed;

[0069] A is the target calcium content of molten steel;

[0070] B is the yield of calcium wire;

[0071] X is the mass of calcium in each meter of calcium wire.

[0072] 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 quality of molten steel and the 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.

[0073] Further, the specific refining process of the whole-process intelligent refining system is as follows:

[0074] Start intelligent refining - automatically collect steel process data - ladle in place - ladle lifting - temperature measurement, sampling, oxygen determination - calculate aluminum oxygen heating - side blowing argon regulation - pre-vacuum - oxygen blowing decarburization - vacuum holding - alloy ratio - breaking vacuum - temperature measurement, sampling - ladle reset - bottom blowing argon regulation - automatic wire feeding - soft blowing end closing argon - production performance automatic upload - ladle outbound.

[0075] A complete and coherent whole-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.

[0076] Compared with the prior art, the present application has the beneficial effects that: the present application realizes precise matching and collaborative operation of parameters in each link by precisely controlling the aluminum thermal reaction to heat the molten steel, and combining with intelligent decarburization, alloying, wire feeding and the like based on real-time data of the molten steel, significantly improves the molten steel quality stability, 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, optimizes production management, and comprehensively enhances the comprehensive benefits and competitiveness of the steelmaking process. BRIEF DESCRIPTION OF DRAWINGS

[0077] 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.

[0078] Figure 1 The present application is a structural schematic diagram. DETAILED DESCRIPTION

[0079] In order to make the purpose, technical solutions 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 do not 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 belong to the scope of protection of the present application.

[0080] The present application provides a full-process intelligent refining system applied to an RH furnace, as shown in Figure 1 The specific modules include the following:

[0081] The data acquisition module is used to acquire real-time refining related data in the furnace, and to send the acquired data to the temperature control module, the intelligent argon blowing module, the vacuum control module, the decarburization control module, the alloy calculation module and the wire feeding control module as needed.

[0082] The data acquisition module acquires data through an industrial robot, the robot is equipped with a temperature sensor and a sampling device, and acquires data through multi-degree-of-freedom movement of the mechanical arm, and stores the acquired data into a business database.

[0083] The temperature control module establishes a molten steel heating model through an algorithm based on real-time acquisition of molten steel temperature data and molten steel process information, and calculates the oxygen blowing amount and the aluminum particle addition amount to control the molten steel temperature.

[0084] The operation process of the temperature control module includes the following steps:

[0085] obtain real-time temperature data of the molten steel;

[0086] When the temperature is in the preset temperature range, the difference between the target temperature and the real-time temperature is calculated, and the aluminum particles and the oxygen blowing amount to be added are calculated according to the difference, which is calculated by the following formula:

[0087]

[0088]

[0089] wherein, represents the aluminum particles required for the molten steel to be heated up;

[0090] represents the target temperature of the heating up;

[0091] represents the measured temperature of the arrival station;

[0092] s represents the heating temperature of the molten steel caused by the complete reaction of 1 kg of aluminum particles;

[0093] represents the oxygen blowing amount required for the molten steel heating up reaction;

[0094] represents the ratio of the theoretical oxygen mass to the aluminum particle mass;

[0095] represents the oxygen density;

[0096] represents the ratio of the oxygen amount entering the molten steel to participate in the reaction to the total oxygen blowing amount.

[0097] Specifically, the equation of the aluminothermic reaction is:

[0098]

[0099] It can be known that 2 moles of Al consume 3 moles of O in the reaction, so the theoretical oxygen mass is the ratio of the aluminum particle mass :

[0100]

[0101] Therefore, the theoretical oxygen demand amount of the aluminothermic reaction In the actual oxygen blowing process, the oxygen blown out from the oxygen blowing equipment cannot all enter the molten steel to participate in the reaction, and part of the oxygen may be retained in the furnace gas without really entering the molten steel. For example, if the total oxygen blowing amount is , wherein the oxygen amount entering the molten steel to participate in the reaction is , then is introduced​​​​ The actual oxygen amount required to be blown in can be calculated by the formula

[0102] The oxygen content in the molten steel after the actual oxygen blown in is calculated by the following formula

[0103]

[0104] Wherein, the oxygen density

[0105] V represents the volume of the oxygen blown in;

[0106] M represents the mass of the molten steel;

[0107] When the mass of the molten steel is 130t, and the oxygen blown in is 1m 3 The oxygen content in the molten steel calculated by the oxygen blown in is:

[0108] .

[0109] The total value of the oxygen content in the molten steel and the residual oxygen in the vacuum chamber is calculated, when the total value is greater than the required oxygen blown in, the decarburization control module updates the residual oxygen content in the molten steel as the difference between the total value and the oxygen blown in, and outputs the aluminum particle addition amount and the residual oxygen content in the molten steel;

[0110] When the total value is less than or equal to the required oxygen blown in, the decarburization control module updates the residual oxygen content in the molten steel as 0, and outputs the aluminum particle addition amount and the oxygen blown in.

[0111] The intelligent argon blowing module is used for processing and analyzing the image of the liquid surface of the ladle to adjust the argon flow in real time.

[0112] Specifically, the intelligent argon blowing module includes the following units:

[0113] The image processing unit is used for real-time acquisition and processing of the image of the liquid surface of the ladle.

[0114] Through the contour segmentation and region statistics method, the coverage range of the side blowing stirring is analyzed. After the camera is installed, the system sets the 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) according to different process stages, for example, the normal smelting process requires the coverage rate to be greater than or equal to 60%, and the decarburization stage requires the coverage rate to be greater than or equal to 85%.

[0115] The data processing unit is used for analyzing and calculating the data acquired by the image processing unit to determine the adjustment direction of the argon flow.

[0116] ​​​​The unit automatically increases the argon flow rate when the current coverage is lower than the process set standard according to the real-time feedback coverage data. To prevent overshooting, the system sets an adjustable range for argon flow rate under each process state, for example, the flow rate adjustment range for the vacuum stage is set to 60-100 Nm 3 / h (the specific range can be set according to equipment and process requirements).

[0117] Argon regulation unit automatically adjusts the argon flow rate according to the adjustment direction of the argon flow rate.

[0118] System alarm unit issues an alarm in abnormal situations to ensure the safe operation of the system, including the following two abnormal processing mechanisms:

[0119] 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 rate is adjusted to avoid misoperation.

[0120] 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 rate within a range of ±10% of the basic value, while issuing a warning signal to prompt the staff to check the image equipment.

[0121] 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.

[0122] 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 realize rapid compensation according to the pressure change, so as to provide continuous and stable vacuum conditions for metallurgical reactions such as degassing and decarburization, effectively improving the purity of molten steel.

[0123] 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):

[0124] 1. When starting to vacuum, start the 5a level pump;

[0125] 2. When the vacuum degree reaches 80 kPa, start the 5b level pump;

[0126] 3. When reaching 40 kPa, start the 4a level pump;

[0127] 4. When reaching 30 kPa, start the 4b level pump;

[0128] 5. When reaching 8 kPa, start the s3 level pump;

[0129] 6. When 2.5 kPa is reached, turn on the s2 stage pump;

[0130] 7. When 0.5 kPa is reached, start the s1 stage pump.

[0131] 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 disposal" mechanism, which includes:

[0132] Leakage feature recognition:

[0133] 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.

[0134] Monitor the data of the pipeline pressure sensor. The pressure near the leakage point will abnormally rise due to air infiltration.

[0135] The system integrates the above information to determine the leakage location and severity in real time, such as distinguishing between minor leaks and serious leaks.

[0136] Compensation and emergency disposal strategy:

[0137] Minor leak (vacuum drop rate < P1 Pa / min, P1 value is 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;

[0138] Serious leak (vacuum drop rate ≥ P2 Pa / min, P2 value is 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 leakage area (if the pipeline is segmented), and increasing the vacuum pump pumping speed to the maximum to maintain system safety.

[0139] Decarburization control module, used to calculate the oxygen blowing amount required for decarburization according to the carbon content of molten steel, and to regulate the decarburization reaction process according to the oxygen blowing amount.

[0140] 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 requirement of molten steel carbon content.

[0141] The decarburization amount is calculated as follows:

[0142] ;

[0143] Where, represents the total amount of decarburization required;

[0144] represents the initial carbon content of molten steel;

[0145] Ctarget represents the target carbon content of the molten steel;

[0146] Ctarget+ΔC represents the carbon increment of the molten steel after alloying.

[0147] The decarburization reaction equation is:

[0148] ;

[0149] From the above decarburization reaction equation, 1 mole of C is consumed for 1 mole of O in the reaction, therefore, the theoretical oxygen mass and the carbon mass ratio is:

[0150] .

[0151] The oxygen blowing amount required for decarburization is calculated according to the total amount of decarburization required and the ratio of the theoretical oxygen mass to the carbon mass :

[0152] .

[0153] The alloy calculation module is configured to establish an alloy model according to the target value of the composition of the molten steel and the yield to calculate the alloy addition amount.

[0154] Specifically, according to the initial composition of the molten steel and the target composition requirement, the type and quantity of alloy addition are accurately calculated to realize accurate alloy addition and ensure that the composition of the molten steel meets the production standard. The yield of the alloy in the RH furnace is relatively stable, and the alloy addition amount can be accurately calculated by establishing a mathematical model based on the mechanism, then accurately added by the alloy weighing and adding system, and adjusted in real time according to the composition monitoring data feedback. The alloy model established according to the yield and the target value of the alloy element is as follows:

[0155] ;

[0156] wherein, Qi represents the addition amount of the i-th alloy;

[0157] Ci represents the initial content of the required alloy element in the molten steel;

[0158] Ci+ represents the final content of the required alloy element in the molten steel;

[0159] Yi represents the yield of the required element in the i-th alloy;

[0160] Xi represents the mass fraction of the required element in the i-th alloy.

[0161] The feeding control module is used to dynamically set the feeding speed, length and timing according to the refining requirements of the molten steel.

[0162] Specifically, according to the refining requirements of the molten steel, the feeding speed, length and timing of the feeding machine 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 the composition and temperature of the molten steel, the feeding parameters are determined by using an algorithm, the feeding machine executes the operation through a high-precision speed and length control device (encoder), and the position monitoring device feeds back the feeding state, so as to ensure the accurate and continuous process.

[0163] The essence of calcium feeding operation is to provide sufficient calcium elements to the molten steel through calcium wire to meet the requirements of inclusion modification (such as Al2O3→12CaO 7Al2O3) or fine adjustment of the composition of the molten steel. For inclusion modification, the required feeding length can be classified according to the steel grade, and a standard feeding amount database is established for query. For composition fine adjustment, the basic calculation formula of the feeding length is:

[0164] L=(A×m) / (B×X);

[0165] L is the length of calcium wire to be fed (m);

[0166] A is the target calcium content of the molten steel (%), which needs to be determined according to the process requirements of the steel grade;

[0167] M is the mass of the molten steel (kg);

[0168] B is the calcium wire yield (%), which needs to be combined with the process measurement, such as the RH vacuum calcium feeding yield, which is usually 20%~35%;

[0169] X is the mass of calcium in each meter of calcium wire (kg / m).

[0170] The intelligent control module generates control instructions based on all other modules to control the operation of the system.

[0171] The ladle car control module is used to collect the distance parameters between the ladle car and the predicted markers in real time by using a laser range finder, and simultaneously analyze the surrounding environment information by using an image processing algorithm, so as to realize the positioning and intelligent walking control of the ladle car.

[0172] Specifically, the module adopts laser positioning technology, integrates laser range finder for real-time detection and image processing auxiliary judgment, realizes high-precision positioning of the ladle car and intelligent walking control. The laser range finder collects the distance parameters of the ladle car and the preset markers in real time, and synchronously analyzes the surrounding environment information such as track obstacles by using image processing algorithms (such as YOLOv5, Faster R-CNN). The system dynamically adjusts the driving system by fusing multi-source data, ensures the positioning accuracy and safe driving of the ladle car, avoids the influence of position deviation on the refining process, and provides a stable foundation for the subsequent process.

[0173] 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 requirements of the refining process.

[0174] Specifically, the module uses hydraulic or electric lifting mechanism as power source, and real-time monitors the lifting height of the ladle through displacement sensor. The control system adjusts the operation of the lifting mechanism according to the requirements of the refining process, so as to realize stable and accurate lifting of the ladle.

[0175] Further, the specific refining process of the whole-process intelligent refining system is as follows:

[0176] Start intelligent refining - automatically collect steel process data - ladle in place - ladle lifting - temperature measurement, sampling, oxygen determination - calculate aluminum oxygen heating - side blowing argon regulation - pre-vacuum - oxygen blowing decarburization - vacuum keeping - alloy ratio - breaking - temperature measurement, sampling - ladle reset - bottom blowing argon regulation - automatic wire feeding - soft blowing end closing argon - production performance automatic uploading - ladle outbound.

[0177] It should be noted that the present application is not limited to the above-mentioned embodiments. The above-mentioned embodiments are only examples, and embodiments having the same technical idea and playing the same role and effect within the scope of the technical solution of the present application are all included in the technical scope of the present application. In addition, within the scope of the main idea of the present application, various modifications of the embodiments that can be thought of by those skilled in the art, and other ways constructed by combining part of the components in the embodiments are also included in the scope 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 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. Based on this difference, calculate the amount of aluminum granules and oxygen to be added, 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; This 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. 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. 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 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.

5. 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.

6. 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.

7. 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; 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.

8. 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.

Images