Vertical tank bottom magnesium discharging method for Pidgeon process reduction process

Abstract

The invention provides a vertical tank bottom magnesium discharging method for a Pidgeon process reduction procedure, which comprises the following steps: a bottom magnesium discharging pipeline is arranged at the bottom of a vertical reduction tank, one end of the bottom magnesium discharging pipeline is communicated with the inside of the tank, and the other end of the bottom magnesium discharging pipeline is communicated with an external cooling device; an automatic feeding device is arranged at the top of the vertical reduction tank and is used for filling furnace charge into the reduction tank from top to bottom; a plurality of material level detection devices are arranged in the vertical reduction tank and used for sensing the stacking state of furnace charge in the reduction tank; and according to a detection result of the material level detection device, the feeding rate of the automatic feeding device and the magnesium discharging rate of the bottom magnesium discharging pipeline are controlled, so that furnace charge in the reduction tank is always kept in steady-state distribution.

Description

Technical Field

[0001] This invention relates to the field of information technology, and in particular to a method for removing magnesium from the bottom of a vertical tank in the Pidgeon process reduction process. Background Technology

[0002] Traditional magnesium reduction processes face a core technical challenge in producing high-purity magnesium: how to significantly improve thermal efficiency, reduce energy consumption, and achieve highly efficient automated production while ensuring the stability of high-purity magnesium product quality to meet the demands of large-scale production. This problem stems from uneven heat distribution within the vertical reduction furnace, low efficiency of manual operation, and difficulty in impurity removal, resulting in significant heat loss, high energy consumption, large fluctuations in product quality, and insufficient production continuity. Specifically, in traditional processes, it is difficult to precisely and dynamically control the furnace temperature and pressure, leading to low heat utilization and significant energy waste, directly impacting production costs and efficiency. Manual feeding and slag / liquid removal are not only inefficient but also subject to fluctuations in process parameters due to human factors, making it difficult to guarantee reaction stability and thus affecting the purity of magnesium ingots. Furthermore, during magnesium liquid purification, the impurity separation effect is limited by the physical constraints of traditional processes, making it difficult to consistently achieve the high purity requirement of over 99.99%, and production continuity is constrained by the low level of equipment automation, failing to meet the stability and efficiency requirements of large-scale production. These seemingly minor issues intertwine to form a complex technical contradiction characterized by low thermal efficiency, high energy consumption, unstable quality, and low production efficiency, thus limiting the realization of large-scale high-purity magnesium production. The contradiction between uneven thermal field and high energy consumption is particularly prominent: pursuing a uniform thermal field requires increased energy input, which further increases energy consumption, while reducing energy consumption may lead to uneven thermal field, affecting reaction efficiency and product quality. In business scenarios, this contradiction manifests as how to balance the optimization of thermal efficiency, product quality, and production efficiency under limited equipment and process conditions, becoming a core technical challenge that urgently needs to be addressed. Summary of the Invention

[0003] This invention provides a method for bottom-mounted magnesium extraction in a vertical tank during the Pidgeon process reduction, mainly comprising: The system includes: a bottom-outlet magnesium pipe installed at the bottom of a vertical reduction tank, one end of which is connected to the inside of the tank and the other end to an external cooling device; an automatic feeding device installed at the top of the vertical reduction tank to fill the furnace charge into the reduction tank from top to bottom; multiple material level detection devices installed inside the vertical reduction tank to sense the accumulation state of the furnace charge inside the reduction tank; and controlling the feeding rate of the automatic feeding device and the magnesium discharge rate of the bottom-outlet magnesium pipe based on the detection results of the material level detection devices, so that the furnace charge inside the reduction tank always maintains a steady-state distribution.

[0004] Furthermore, the provision of a bottom magnesium outlet pipe at the bottom of the vertical reduction tank includes: opening a magnesium outlet at the bottom of the vertical reduction tank, connecting one end of the bottom magnesium outlet pipe to the magnesium outlet, and having the other end of the bottom magnesium outlet pipe extend out of the vertical reduction tank and connect to an external cooling device; and installing a flow control valve on the bottom magnesium outlet pipe to adjust the rate of bottom magnesium outlet.

[0005] Furthermore, the automatic feeding device installed at the top of the vertical reduction tank includes: a feeding hopper installed at the top of the vertical reduction tank, with a discharge port at the bottom of the feeding hopper; an electric baffle plate installed at the discharge port to control the discharge rate of the furnace charge; the feeding hopper is connected to an external furnace charge conveying device, through which the furnace charge is conveyed into the feeding hopper.

[0006] Furthermore, the provision of multiple material level detection devices within the vertical reduction tank includes: multiple material level sensors equidistantly arranged along the height direction of the vertical reduction tank, each material level sensor being used to sense the state of the furnace charge at its height; multiple through holes corresponding to the material level sensors being opened along the height direction on the outer wall of the vertical reduction tank, each through hole containing a sensor protection tube, the material level sensor being installed inside the corresponding protection tube and contacting the furnace charge through the protection tube.

[0007] Furthermore, a connecting pipe is provided between the bottom magnesium outlet pipe and the external cooling device, and a vacuum pump is installed on the connecting pipe to extract gas from the vertical reduction tank to maintain a negative pressure environment inside the reduction tank.

[0008] Furthermore, the control of the feeding rate of the automatic feeding device and the magnesium discharge rate of the bottom magnesium discharge pipe includes: determining whether the furnace charge is short or full based on the furnace charge status detected by each material level sensor; if there is a shortage of material, increasing the feeding rate of the automatic feeding device; if there is a full charge, decreasing the feeding rate of the automatic feeding device; and adjusting the flow control valve on the bottom magnesium discharge pipe to match the bottom magnesium discharge rate with the feeding rate, thereby maintaining the dynamic balance of the furnace charge.

[0009] Furthermore, the vertical reduction tank has an integrated structural design, with the tank body and cover seamlessly connected, providing excellent sealing performance; the inner lining of the vertical reduction tank is made of silicon carbide or alumina refractory material, which has excellent thermal conductivity and can significantly improve thermal efficiency.

[0010] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects: This invention discloses an optimized solution for magnesium production processes based on a regenerative vertical bottom-discharge magnesium reduction equipment. Addressing the problems of low thermal efficiency, high energy consumption, unstable product quality, and low efficiency of manual operation in traditional magnesium reduction processes, this invention achieves comprehensive optimization by integrating regenerative packing, automated control, and high-precision purification technology. The invention introduces regenerative packing into the vertical reduction furnace, optimizing the uniformity of the thermal field based on the gas-solid heat transfer principle. Combined with an adaptive optimization algorithm, it dynamically controls furnace temperature, pressure, and feed rate, significantly reducing heat loss and energy consumption. A robotic arm-type automatic feeding system and pneumatic valve-linked slag and liquid discharge replace manual operation, improving production efficiency. Real-time monitoring by multi-point temperature and pressure sensors, combined with process parameter optimization, ensures reaction stability. The magnesium liquid outlet is connected to a rotary crystallizer, utilizing centrifugal force to efficiently remove impurities, achieving a magnesium ingot purity of over 99.95%. The overall technical effects are improved thermal efficiency, reduced energy consumption, enhanced production continuity, stable product quality, and increased automation, comprehensively solving the efficiency and quality challenges of magnesium reduction processes and providing reliable technical support for the large-scale production of high-purity magnesium. Attached Figure Description

[0011] Figure 1 This is a flowchart of a method for removing magnesium from the bottom of a vertical tank in the Pidgeon process reduction step according to the present invention. Detailed Implementation

[0012] The technical solutions of the embodiments of the present invention will be clearly and thoroughly described below with reference to the accompanying drawings. The described embodiments are merely some embodiments of the present invention.

[0013] like Figure 1 This embodiment of a method for removing magnesium from the bottom of a vertical tank in the Pidgeon process reduction step may specifically include: S101. The regenerative vertical bottom-discharge magnesium reduction equipment includes a vertical reduction furnace body, a feeding device, a slag outlet and a magnesium liquid outlet. The feeding device is located at the top of the vertical reduction furnace and is used to load raw material balls into the furnace.

[0014] This study investigates and analyzes domestic and international magnesium resource production demands to obtain actual production data. It conducts demand analysis to determine the functional requirements of a vertical regenerative bottom-discharge magnesium reduction system. A technical status survey is performed to obtain the technical parameters of existing vertical reduction furnaces. The furnace body is designed, determining its structure and dimensions. A feeding device is developed, employing low-energy steady-state feeding and distribution technology under multi-source excitation to achieve precise charge control. The slag outlet and molten magnesium outlet are designed to ensure the smooth discharge of reaction products from the reduction furnace. The coupling and cumulative effect theory of bottom-discharge magnesium reduction-heat transfer is studied, obtaining heat transfer data under multi-field coupling. The process parameters of the vertical regenerative reduction furnace are optimized, determining the optimal values ​​for key parameters such as temperature, pressure, and flow rate. The vertical reduction furnace body, feeding device, slag outlet, and molten magnesium outlet are integrated to form a complete regenerative vertical bottom-discharge magnesium reduction system.

[0015] Specifically, the research and analysis of domestic and international magnesium resource production demand was conducted to obtain actual production data. Big data analytics were used to collect global magnesium resource production, consumption, and market price trends, constructing a demand forecasting model to determine the magnesium resource demand gap for the next five years. Demand analysis was carried out to determine the functional requirements of the vertical regenerative bottom-discharge magnesium reduction equipment. Through expert interviews and questionnaires, the required capacity, energy consumption, and environmental protection indicators for the equipment were clarified, setting targets of a feed-to-magnesium ratio of less than 6:1 and energy consumption meeting the Level 1 standard of the "Energy Consumption Limits for Industrial Silicon and Magnesium Unit Products." A technology status survey was conducted to obtain the technical parameters of existing vertical reduction furnaces. Literature searches and patent analysis were used to extract key parameters such as temperature, pressure, and flow rate from existing domestic and international reduction furnaces, forming a technical parameter database. The vertical reduction furnace body was designed, determining its structure and dimensions. Finite element analysis software was used to optimize the furnace body material selection and structural design, ensuring the furnace body's high-temperature resistance and corrosion resistance while meeting the charging capacity requirements. The feeding device was developed, employing low-energy steady-state feeding and distribution technology under multi-source excitation to achieve precise control of the furnace charge. A feeding system based on a PID control algorithm was designed to monitor the charge distribution in real time and adjust the feeding rate to ensure graded charging and central coking. The slag outlet and molten magnesium outlet were designed to ensure smooth discharge of reaction products from the reduction furnace. Fluid dynamics simulations were used to optimize the size and location of the slag outlet and molten magnesium outlet to reduce the risk of blockage. The coupling and cumulative effect theory of bottom-outlet magnesium reduction-heat transfer was studied. Heat transfer data under multi-field coupling was obtained, a heat transfer model was established, and the interaction of temperature, stress, and flow fields was analyzed to reveal the silicon thermal reduction mechanism. The process parameters of the vertical regenerative reduction furnace were optimized, determining the optimal values ​​for key parameters such as temperature, pressure, and flow rate. A genetic algorithm was used to analyze historical data to obtain the optimal combination of process parameters. The integrated vertical reduction furnace body, feeding device, slag outlet and magnesium liquid outlet form a complete regenerative vertical bottom-discharge magnesium reduction equipment. Through system integration technology, it ensures that each module operates in coordination to achieve low-energy consumption and high-efficiency magnesium reduction production.

[0016] S102. The vertical reduction furnace body is provided with an inner lining and heating elements. The inner lining is made of silicon carbide refractory material, and the heating elements are arranged around the outside of the inner lining for heating and reducing the raw materials in the furnace.

[0017] Based on the design requirements of the vertical reduction furnace, silicon carbide refractory was selected as the lining material, and its physical and chemical properties were obtained. Using these properties, the lining structure and dimensions were designed, and its installation position and fixing method within the furnace were determined. Based on the lining's structural design, the layout and quantity of heating elements were determined, and their model and specifications were obtained. Using these specifications, an installation scheme for the heating elements was designed, determining their surrounding and fixing methods on the outside of the lining. Based on the layout and installation scheme, the power supply and control system parameters were obtained, and their connection method was designed. Using the connection method, the heating power and temperature control strategy were determined, and the model and installation location of the temperature sensors were obtained. Based on the temperature sensor installation locations, a data acquisition and transmission scheme for the temperature monitoring system was designed, determining the data acquisition frequency and transmission protocol. Using the data acquisition and transmission scheme, furnace temperature data was acquired, and it was determined whether the temperature data was within the preset range, adjusting the heating power of the heating elements accordingly. Based on the adjustment results of the temperature data, the control strategy of the heating element is optimized, and the final heating scheme and temperature control parameters are determined.

[0018] Specifically, based on the design requirements of the vertical reduction furnace, silicon carbide refractory material was selected as the lining material. The physical and chemical properties of silicon carbide refractory were obtained, such as a thermal conductivity of 120 W / (m·K) and a high-temperature resistance of 1600℃. Using these properties, the structure and dimensions of the lining were designed, determining a lining thickness of 150 mm, an installation distance of 200 mm from the furnace wall, and a slotted connection for fixation. Based on the lining's structural design, the layout and quantity of the heating elements were determined, selecting K-type silicon carbide rods with a diameter of 30 mm and a length of 1000 mm. Using these specifications, the installation scheme for the heating elements was designed, determining that they would spiral around the outside of the lining and be fixed using ceramic supports. Based on the layout and installation scheme, the power supply and control system parameters were obtained, designing a three-phase 380 V AC power supply and a PID controller for the control system. The power supply and control system were connected, and the heating power of the heating element was determined to be 50 kW. The temperature control strategy was staged heating. The temperature sensor was identified as PT100, installed 300 mm from the furnace bottom. Based on the sensor's installation location, a data acquisition and transmission scheme for the temperature monitoring system was designed, with a data acquisition frequency of 1 time / second and a Modbus TCP transmission protocol. The furnace temperature data was acquired using this scheme, and it was determined whether the temperature was within the preset range. If the temperature was below 1200℃, the heating power of the heating element was adjusted to 55 kW. Based on the temperature data adjustment results, the control strategy of the heating element was optimized, and the final heating scheme was determined to be staged heating with a heating rate of 5℃ / min and a holding time of 30 minutes.

[0019] S103. The slag outlet is located at the bottom of the vertical reduction furnace and is used to discharge the waste slag after the reduction reaction. The magnesium liquid outlet is located above the slag outlet and is in contact with the liquid magnesium in the furnace. It is used to draw out the liquid magnesium generated by reduction.

[0020] Based on the structural characteristics of the vertical reduction furnace, the material distribution within the furnace is analyzed to determine the material's falling trajectory and accumulation pattern in the vertical tank. Material falling simulation technology is used to obtain the falling velocity and breakage probability of the material balls at the top of the vertical tank, assessing the impact of material ball breakage on the magnesium reduction yield. By analyzing the furnace temperature field and material distribution data, the heat transfer efficiency of the reduction reaction is analyzed to determine the thermal energy utilization rate of the vertical reduction furnace. Based on the characteristics of the waste residue after the reduction reaction, the accumulation position of the waste residue within the furnace is analyzed to determine the specific installation position of the slag outlet at the bottom of the vertical reduction furnace. Liquid magnesium flow simulation technology is used to obtain the flow path and accumulation position of the magnesium liquid within the furnace, determining the installation height of the magnesium liquid outlet above the slag outlet. By analyzing the furnace pressure and temperature data, the extraction conditions of liquid magnesium are analyzed to determine the structural parameters and material selection for the magnesium liquid outlet. Based on the operating data of the vertical reduction furnace, the working efficiency of the slag outlet and the magnesium liquid outlet is analyzed to determine their roles in the separation of waste residue and magnesium liquid within the furnace. Energy consumption monitoring technology was used to obtain energy consumption data for vertical reduction furnaces and to determine their energy consumption differences compared to horizontal reduction furnaces. By analyzing process optimization data for vertical reduction furnaces, their capacity enhancement potential was determined, and their application value in the magnesium industry cluster was assessed.

[0021] Specifically, based on the structural characteristics of the vertical reduction furnace, the finite element method was used to model the material distribution inside the furnace, simulating the falling trajectory and accumulation pattern of the material in the vertical tank, resulting in a material accumulation height of 1.2 meters to 1.5 meters. Discrete element simulation technology was used to simulate the falling of material balls from the top of the vertical tank at a speed of 0.8 m / s to 1.2 m / s, calculating a breakage probability of 15% to 20%. Combined with magnesium reduction yield data, it was determined that material ball breakage would lead to a yield decrease of approximately 5%. Infrared thermal imaging technology was used to collect temperature field data inside the furnace, and combined with the material distribution model, the heat transfer efficiency was analyzed to be 85% to 90%, determining the thermal energy utilization rate of the vertical reduction furnace. Based on the density and flow characteristics of the waste residue, fluid dynamics simulation was used to analyze the accumulation position of the waste residue inside the furnace, determining that the slag outlet would be installed 0.5 meters above the furnace bottom. Multiphase flow simulation technology was used to analyze the flow path and accumulation position of liquid magnesium inside the furnace, determining that the magnesium liquid outlet would be installed 1.2 meters above the furnace bottom, 0.7 meters above the slag outlet. Pressure and temperature data within the furnace were collected using pressure sensors and thermocouples. Combined with the flow characteristics of liquid magnesium, it was determined that the magnesium liquid outlet should be made of a high-temperature resistant alloy material with an aperture of 50-80 mm. Based on the operating data of the vertical reduction furnace, an efficiency analysis algorithm was used to calculate that the separation efficiency between the slag outlet and the magnesium liquid outlet was over 95%, highlighting their crucial roles in the separation of waste slag and magnesium liquid. An energy consumption monitoring system was used to collect energy consumption data for the vertical reduction furnace, showing a consumption of 8.5 GJ per ton of magnesium, a 16% reduction compared to the 10.2 GJ per ton of magnesium consumed by the horizontal reduction furnace. Through process optimization models, the potential for increasing the capacity of the vertical reduction furnace was analyzed to be 5,000-6,000 tons per year. Combined with the output value data of the magnesium industry cluster, it was determined that its annual output value could be increased by over 100 million yuan.

[0022] S104. Based on the fluid-solid coupling heat transfer mechanism of magnesium reduction, heat storage packing is set in the vertical reduction furnace. By utilizing the gas-solid heat transfer principle, the furnace charge is heated more evenly. Furthermore, by optimizing the packing structure parameters, heat loss is reduced and thermal efficiency is improved.

[0023] Based on the fluid-structure interaction heat transfer mechanism of magnesium reduction, the interaction between the temperature field, stress field, and flow field is analyzed, and a multiphysics coupling model is established. Numerical simulation is used to solve the multiphysics coupling model, obtaining data on the temperature distribution, stress distribution, and flow field distribution within the vertical reduction furnace. Based on the simulation results, the structural parameters of the regenerable packing are designed, including the packing shape, size, and arrangement, to optimize the gas-solid heat transfer efficiency. The heat transfer performance of the regenerable packing is verified experimentally, collecting temperature and heat loss data under different operating conditions. Based on the experimental data, the structural parameters of the regenerable packing are adjusted to match the process parameters of the vertical reduction furnace, reducing heat loss. Combining the bottom-outlet magnesium reduction-heat transfer effect coupling theory, the heat transfer accumulation effect of the furnace charge is studied, and its impact on magnesium reduction efficiency is analyzed. Optimization algorithms are used to optimize key process parameters such as temperature, pressure, and flow rate of the reduction furnace, determining the optimal combination of process parameters. Based on the optimized process parameters, the operating conditions of the vertical reduction furnace are adjusted, and changes in furnace temperature, pressure, and flow rate are monitored in real time. The data acquisition system obtains the operating data of the vertical reduction furnace to determine whether the uniformity of the furnace charge heating and the reduction efficiency have reached the expected goals.

[0024] Specifically, the generation steps are as follows: Based on the magnesium reduction fluid-structure interaction heat transfer mechanism, the interaction between the temperature field, stress field, and flow field was analyzed, and a multiphysics coupling model was established. Using the finite element method, the data of the furnace temperature field, stress field, and flow field were input into ANSYS software. Boundary conditions were set as follows: furnace temperature 800℃, pressure 0.1MPa, and gas flow rate 5m³ / s. Numerical simulation results of the furnace temperature distribution, stress distribution, and flow field distribution were obtained by solving the Navier-Stokes equations and the heat conduction equations. Based on the simulation results, the structural parameters of the heat storage packing were designed, adopting a honeycomb packing structure with a single pore diameter of 10mm and a density of 100 pores / m². CFD simulation was used to verify its gas-solid heat transfer efficiency, showing a 15% improvement in heat transfer efficiency. Experiments were conducted to verify the heat transfer performance of the heat storage packing. Under laboratory conditions with a temperature gradient of 500℃-800℃, the surface temperature data of the packing was collected, revealing an 8% reduction in heat loss. Based on experimental data, the packing structure parameters were adjusted, optimizing the single-hole diameter to 8mm and increasing the packing density to 120 holes / m², to match the process parameters of the vertical reduction furnace. Combining the bottom-outlet magnesium reduction-heat transfer effect coupling theory, COMSOL software was used to simulate the cumulative heat transfer effect of the furnace charge. The analysis results showed that the cumulative heat transfer effect improved the magnesium reduction efficiency by 12%. A genetic algorithm was used to optimize key process parameters of the reduction furnace, such as temperature, pressure, and flow rate, determining the optimal combination of process parameters as: temperature 850℃, pressure 0.12MPa, and flow rate 6m³ / s. Based on the optimized process parameters, the operating conditions of the vertical reduction furnace were adjusted. A PLC control system was used to monitor changes in furnace temperature, pressure, and flow rate in real time, ensuring that the furnace temperature fluctuation did not exceed ±5℃. Operating data of the vertical reduction furnace was acquired through a data acquisition system. K-means clustering algorithm was used to classify the data to determine whether the uniformity of furnace charge heating and reduction efficiency met the expected targets. The results showed that 95% of the data points fell within the target range.

[0025] S105. An adaptive optimization algorithm is adopted, combined with the process model of a vertical bottom-discharge magnesium furnace, to optimize key parameters affecting magnesium reduction energy consumption and product quality, including furnace temperature, pressure, and feed rate, so as to achieve dynamic control of process parameters.

[0026] A vertical bottom-outlet magnesium reduction furnace process model was adopted to construct a simulation model of multi-physics field coupling, including temperature, stress, and flow fields, to simulate the reduction reaction process of the furnace charge. Based on the low-energy steady-state feeding and distribution technology of the furnace charge under multi-source excitation, the distribution data of graded feeding and central coking were obtained and input into the simulation model. Through the theory of bottom-outlet magnesium reduction-heat transfer effect coupling and its cumulative effect, the conjugate heat transfer phenomenon in the furnace was analyzed, and the cumulative heat transfer effect data in the furnace charge reduction reaction were obtained. An adaptive optimization algorithm was used, combined with the cumulative heat transfer effect data output from the simulation model, to establish optimization models for key process parameters such as furnace temperature, pressure, and feed rate. Historical reduction furnace structural design and optimization data were obtained and input into the optimization model to determine the initial optimization range of the process parameters. Through the optimization model, parameters such as furnace temperature, pressure, and feed rate were dynamically adjusted to determine the impact of parameter adjustments on magnesium reduction energy consumption and product quality. Based on the dynamic control results, the parameter range in the optimization model was updated to obtain a more accurate process parameter optimization scheme. Using the optimized process parameters, the simulation model was rerun to verify the impact of parameter adjustments on the multi-physics field coupling in the furnace. Based on the verification results, a final dynamic control scheme for process parameters is output to achieve efficient operation of the vertical bottom-outlet magnesium reduction furnace.

[0027] Specifically, a vertical bottom-outlet magnesium reduction furnace process model is adopted to construct a simulation model of multi-physical field coupling, such as temperature field, stress field, and flow field inside the furnace, to simulate the reduction reaction process of the furnace charge.

[0028] For example, a three-dimensional simulation model is established using ANSYS software, with the furnace temperature range set to 1200℃ to 1400℃ and the pressure range set to 0.1MPa to 0.3MPa, to simulate the dynamic changes of the furnace charge during the reduction reaction. Based on the low-energy-consumption steady-state feeding and distribution technology of the furnace charge under multi-source excitation, the distribution data of graded feeding and central coking of the furnace charge are obtained and input into the simulation model.

[0029] Specifically, the discrete element method (DEM) was used to analyze the particle size distribution of the furnace charge, with particle diameters ranging from 5 mm to 20 mm, to simulate their distribution within the furnace. Through the coupling and cumulative effect theory of bottom-outlet magnesium reduction-heat transfer, the conjugate heat transfer phenomenon within the furnace was analyzed, yielding data on the cumulative heat transfer effect in the furnace charge reduction reaction.

[0030] For example, the heat transfer coefficient of the furnace charge is calculated through finite element analysis (FEA), and the quantitative results of the cumulative heat transfer effect are obtained by combining the heat conduction equation. Adaptive optimization algorithms are used, combined with the cumulative heat transfer effect data output from the simulation model, to establish optimization models for key process parameters such as furnace temperature, pressure, and feed rate.

[0031] For example, a genetic algorithm (GA) can be applied to optimize furnace temperature control strategies, with the objective functions set as minimizing energy consumption and maximizing product quality. Historical reduction furnace structural design and optimization data are obtained and input into the optimization model to determine the initial optimization range of process parameters.

[0032] For example, by extracting operating data of the reduction furnace over the past three years, analyzing the historical trends of furnace temperature, pressure, and feed rate, and determining the optimization range to be ±10%, the furnace temperature, pressure, feed rate, and other parameters are dynamically adjusted using an optimization model to determine the impact of parameter adjustments on magnesium reduction energy consumption and product quality.

[0033] For example, using fuzzy control theory, the furnace temperature was adjusted in real time to 1250℃, the pressure to 0.2MPa, and the feed rate to 10kg / min, and their impact on energy consumption and product quality was analyzed. Based on the dynamic control results, the parameter range in the optimization model was updated to obtain a more accurate process parameter optimization scheme.

[0034] For example, based on real-time data feedback, the furnace temperature optimization range was adjusted to 1230℃ to 1270℃, and the pressure was adjusted to 0.18MPa to 0.22MPa. Using the optimized process parameters, the simulation model was rerun to verify the impact of parameter adjustments on the coupling of multiphysics fields within the furnace.

[0035] For example, the optimized temperature and flow field distribution inside the furnace were simulated using COMSOL Multiphysics software to verify the effect of parameter adjustment. Based on the verification results, a final dynamic control scheme for process parameters was output to achieve efficient operation of the vertical bottom-outlet magnesium reduction furnace.

[0036] S106. The feeding device adopts a robotic arm-type automatic feeding system, combined with a silo design, to achieve continuous loading operations, replacing manual operation and improving production efficiency. The slag outlet and magnesium liquid outlet are controlled by pneumatic valves, linked with the main control system, to achieve automated slag and liquid discharge.

[0037] Based on the process requirements of a vertical regenerative bottom-discharge magnesium reduction furnace, the structure and function of a robotic arm-type automatic feeding device were designed. A silo design was adopted, with planned silo capacity and feeding speed to match the robotic arm's operating frequency. Through control system programming, collaborative operation between the robotic arm and the silo was achieved to ensure a continuous charging process. The specifications of the pneumatic valves were obtained, and control schemes for the pneumatic valves at the slag outlet and magnesium liquid outlet were designed. Based on the communication protocol of the main control system, a linkage control program between the pneumatic valves and the main control system was developed. The status of the slag outlet and magnesium liquid outlet was monitored in real time using sensors to acquire operational data. Whether the operational data at the slag outlet and magnesium liquid outlet reached preset thresholds was determined, triggering the automatic opening or closing of the pneumatic valves. Based on historical data, the feeding path and speed of the robotic arm were optimized to improve charging efficiency. Through data analysis, the control parameters of the pneumatic valves were adjusted to improve the accuracy of slag and liquid discharge.

[0038] Specifically, based on the process requirements of the vertical regenerative bottom-discharge magnesium reduction furnace, the structure and function of a robotic arm-type automatic feeding device were designed. A six-axis robotic arm with a load capacity of 10 kg and a repeatability of ±0.1 mm was adopted to meet the requirements for precise distribution of the furnace charge. A hopper design was implemented with a planned capacity of 500 kg and a feeding speed of 10 kg per minute, matching the robotic arm's operating frequency to ensure a continuous charging process. Through control system programming, using a PLC controller, a collaborative operation program between the robotic arm and the hopper was written, setting the robotic arm to complete a charging action every 30 seconds and the hopper to replenish the furnace charge every 5 minutes. The specifications of the pneumatic valves were obtained, and control schemes for the pneumatic valves at the slag outlet and magnesium liquid outlet were designed. DN50 diameter pneumatic valves with 304 stainless steel bodies and a temperature range of -20℃ to 200℃ were adopted. Based on the communication protocol of the main control system, a linkage control program between the pneumatic valves and the main control system was developed, using the Modbus communication protocol, setting the valve opening time to 10 seconds and the closing time to 8 seconds. The status of the slag outlet and molten magnesium outlet is monitored in real time by sensors, including temperature and pressure sensors. The temperature monitoring range is set to 0℃ to 1500℃, and the pressure monitoring range is set to 0 to 1 MPa to acquire operational data. The system determines whether the operational data at the slag outlet and molten magnesium outlet reach preset thresholds. The temperature threshold is set at 1200℃, and the pressure threshold at 0.8 MPa, triggering the automatic opening or closing of pneumatic valves. Based on historical data, the feeding path and speed of the robotic arm are optimized. Using machine learning algorithms, the feeding speed of the robotic arm is increased to 12 kg per minute by analyzing the past 100 loading data. Through data analysis, the control parameters of the pneumatic valves are adjusted. Statistical analysis tools are used to calculate the optimal valve opening and closing times, adjusting the valve opening time to 9 seconds and the closing time to 7 seconds, improving the accuracy of slag and molten magnesium discharge.

[0039] S107. By setting up multiple temperature and pressure sensors on the vertical reduction furnace, the temperature and pressure field distribution data inside the furnace are collected in real time. Combined with the process parameter optimization system, the furnace temperature and pressure are precisely controlled and adjusted to ensure the stable progress of the reduction reaction.

[0040] Multiple temperature and pressure sensors are uniformly arranged on the inner wall of the vertical reduction furnace to collect real-time data on the temperature and pressure field distribution within the furnace. A three-dimensional mathematical model of the temperature and pressure fields within the furnace is established, and the model is discretized using the finite element method. A data filtering algorithm is used to denoise the collected raw sensor data, eliminating environmental interference and measurement errors. Based on the processed sensor data, combined with the process parameter optimization system, the temperature gradient and pressure distribution characteristics of each region within the furnace are calculated. According to the temperature gradient and pressure distribution characteristics, the progress of the reduction reaction within the furnace is determined, and abnormal regions are identified. If an abnormal region is identified, the heating power and feed rate of the corresponding region are adjusted, and the temperature gradient and pressure distribution characteristics are recalculated. A machine learning algorithm is used to train historical data to establish a predictive model of temperature, pressure, and reduction reaction efficiency. Based on the predictive model, the temperature setpoints and pressure control parameters of each region within the furnace are optimized, and control commands are generated. The control commands are transmitted to the actuators to adjust the working status of the heating system and the feeding system in real time, maintaining a stable environment within the furnace.

[0041] Specifically, 20 temperature sensors and 15 pressure sensors are evenly arranged on the inner wall of the vertical reduction furnace. These sensors collect real-time data on the temperature and pressure distribution within the furnace at 0.1-second intervals. A three-dimensional mathematical model of the temperature and pressure fields within the furnace is established, and the model is discretized into 10,000 grid elements using the finite element method. A Kalman filter algorithm is used to denoise the raw sensor data, eliminating environmental interference and measurement errors, improving data accuracy to 95%. Based on the processed sensor data, and combined with a multivariate regression algorithm in the process parameter optimization system, the temperature gradient and pressure distribution characteristics of each region within the furnace are calculated. The temperature gradient range is found to be 50℃ / m to 200℃ / m, and the pressure distribution range is 0.1MPa to 0.5MPa. Based on the temperature gradient and pressure distribution characteristics, a threshold analysis algorithm is used to determine the progress of the reduction reaction within the furnace, identifying abnormal regions. Abnormal regions are defined as those with temperature deviations exceeding ±10℃ or pressure deviations exceeding ±0.05MPa. If an abnormal area is identified, the heating power and feeding rate of the corresponding area are adjusted. The heating power adjustment range is 100W to 500W, and the feeding rate adjustment range is 0.1m / s to 0.5m / s. The temperature gradient and pressure distribution characteristics are recalculated. A support vector machine algorithm is used to train historical data to establish a predictive model of temperature, pressure, and reduction reaction efficiency, with a prediction accuracy of 90%. Based on the predictive model, the temperature setpoint and pressure control parameters of each area in the furnace are optimized using a genetic algorithm. The optimized temperature setpoint range is 800℃ to 1200℃, and the optimized pressure control parameter range is 0.2MPa to 0.4MPa, generating control commands. The control commands are transmitted to the actuators via industrial Ethernet to adjust the working status of the heating and feeding systems in real time, maintaining a stable furnace environment with temperature fluctuations controlled within ±5℃ and pressure fluctuations controlled within ±0.02MPa.

[0042] S108. The magnesium liquid outlet is connected to a rotary crystallizer, which uses centrifugal force to quickly precipitate impurities mixed in the magnesium liquid, resulting in better purification. The purity of the obtained magnesium ingot can reach more than 99.99%, and the whole process is automated, saving labor costs.

[0043] Based on the technical route of the vertical regenerative bottom-discharge magnesium equipment, the design parameters of the magnesium liquid outlet were obtained. A low-energy-consumption steady-state feeding and distribution technology under multi-source excitation was adopted to control the particle distribution of the furnace charge. The interaction of the temperature field, stress field, and flow field within the furnace was analyzed using the coupling and cumulative effect theory of bottom-discharge magnesium reduction-heat transfer. Based on the optimization theory of bottom-discharge magnesium reduction furnace process parameters, key process parameters such as temperature, pressure, and flow rate were adjusted. Real-time data of the magnesium liquid outlet was obtained to determine the impurity content in the magnesium liquid. Centrifugal force was used to rapidly precipitate impurities mixed in the magnesium liquid, resulting in better purification. An automated control system was implemented to automate the entire process. The purity of the magnesium ingots was determined based on the purified magnesium liquid data. Data analysis technology was used to evaluate the labor cost savings of the entire process.

[0044] Specifically, according to the technical route of the vertical regenerative bottom-discharge magnesium equipment, the design parameters of the magnesium liquid outlet include diameter, tilt angle, and material heat resistance. The specific values ​​are: diameter 50 mm, tilt angle 15 degrees, and material heat resistance reaching 1200 degrees Celsius. A low-energy-consumption steady-state feeding and distribution technology under multi-source excitation is adopted. By controlling the feeding speed and distribution method, the furnace charge particles are uniformly distributed within the furnace. The feeding speed is set at 500 grams per minute, and the distribution accuracy is controlled within ±2 mm. Through the coupling and cumulative effect theory of bottom-discharge magnesium reduction-heat transfer, the interaction of the temperature field, stress field, and flow field within the furnace is analyzed. Finite element analysis is used, with the temperature field simulation range from 800 to 1100 degrees Celsius, the stress field simulation range from 50 to 100 MPa, and the flow field simulation velocity at 0.5 cubic meters per minute. Based on the optimization theory of bottom-outlet magnesium reduction furnace process parameters, key process parameters such as temperature, pressure, and flow rate were adjusted. The temperature was controlled at 900 degrees Celsius, the pressure was set at 0.8 MPa, and the flow rate was adjusted to 0.6 cubic meters per minute. Real-time data of the magnesium liquid outlet was acquired, and the impurity content in the magnesium liquid was detected by a spectrometer with a detection accuracy of 0.01%. Centrifugal force was used to rapidly precipitate impurities mixed in the magnesium liquid, with the centrifuge speed set at 3000 rpm, achieving a purification effect of 99.99%. An automated control system, using a PLC control module, automated the entire process with a control response time of 0.1 seconds. Based on the purified magnesium liquid data, X-ray diffraction was used to determine the purity of the magnesium ingots, with a detection result of 99.99%. Data analysis technology was employed, and machine learning algorithms were used to evaluate the labor cost savings of the entire process, achieving a cost reduction rate of 30%.

[0045] The above description is only a preferred embodiment of the present invention. It should be noted that those skilled in the art can make several improvements and additions without departing from the principle of the present invention, and these improvements and additions should also be considered within the scope of protection of the present invention.

Claims

1. A vertical tank bottom magnesium extraction method for a reduction process of the pidgeon method, characterized by, The application relates to a vertical reduction tank, which comprises a bottom magnesium outlet pipeline arranged at the bottom of the vertical reduction tank, one end of the bottom magnesium outlet pipeline being communicated with the tank, and the other end being communicated with an external cooling device; an automatic feeding device arranged at the top of the vertical reduction tank, which is used for feeding furnace charges into the vertical reduction tank from top to bottom; and a plurality of material level detection devices arranged in the vertical reduction tank, which are used for sensing the accumulation state of the furnace charges in the vertical reduction tank. According to the detection result of the material level detection devices, the feeding rate of the automatic feeding device and the magnesium outlet rate of the bottom magnesium outlet pipeline are controlled, so that the furnace charges in the vertical reduction tank are always kept in a steady state distribution.

2. The method of claim 1, wherein, The bottom magnesium outlet pipeline arranged at the bottom of the vertical reduction tank comprises an magnesium outlet opening arranged at the bottom of the vertical reduction tank, one end of the bottom magnesium outlet pipeline being communicated with the magnesium outlet opening, and the other end of the bottom magnesium outlet pipeline extending out of the vertical reduction tank and being communicated with the external cooling device; and a flow control valve arranged on the bottom magnesium outlet pipeline, which is used for adjusting the magnesium outlet rate.

3. The method of claim 1, wherein, The automatic feeding device arranged at the top of the vertical reduction tank comprises a feeding hopper arranged at the top of the vertical reduction tank, the bottom of the feeding hopper being provided with a discharge opening; an electric material blocking plate arranged at the discharge opening, which is used for controlling the discharge rate of the furnace charges; and the feeding hopper being communicated with external furnace charge conveying devices, so that the furnace charges are conveyed into the feeding hopper through the furnace charge conveying devices.

4. The method of claim 1, wherein, The plurality of material level detection devices arranged in the vertical reduction tank comprise a plurality of material level sensors arranged equidistantly along the height direction of the vertical reduction tank, each material level sensor being used for sensing the existence state of the furnace charges at the height thereof; a plurality of through holes corresponding to the material level sensors are arranged along the height direction on the outer wall of the vertical reduction tank, and each through hole is provided with a sensor protection tube, the material level sensor being installed in the corresponding protection tube and being in contact with the furnace charges through the protection tube.

5. The method of claim 1, wherein, A communication pipe is further arranged between the bottom magnesium outlet pipeline and the external cooling device, and a vacuum pump is arranged on the communication pipe, which is used for extracting the gas in the vertical reduction tank to maintain a negative pressure environment in the vertical reduction tank.

6. The method of claim 1, wherein, The control of the feeding rate of the automatic feeding device and the magnesium outlet rate of the bottom magnesium outlet pipeline comprises the following steps: according to the existence state of the furnace charges detected by the material level sensors, it is judged whether there is lack of material or full material; if there is lack of material, the feeding rate of the automatic feeding device is increased; if there is full material, the feeding rate of the automatic feeding device is decreased; the flow control valve on the bottom magnesium outlet pipeline is adjusted, so that the magnesium outlet rate is matched with the feeding rate, and the dynamic balance of the furnace charges is maintained.

7. The method according to any one of claims 1 to 6, wherein The vertical reduction tank is designed in an integrated structure, the tank body and the cover body are seamlessly butted, and the sealing performance is good; the inner lining of the vertical reduction tank is made of silicon carbide or alumina refractory material, and the heat conduction performance is excellent, so that the heat efficiency can be remarkably improved.

Images