Method and device for regulating and controlling thermal stress of furnace body of non-ferrous metal bath smelting furnace

Abstract

The invention relates to the technical field of heavy nonferrous metal pyrometallurgy and process equipment, and discloses a method and device for regulating and controlling thermal stress of a furnace body of a nonferrous metal bath smelting furnace, and the method comprises the steps that a furnace shell is divided into a feeding end area, a middle high heat load area, a copper or lead discharging end area, a nickel discharging end area and other areas in the furnace length direction; dividing areas along the furnace width direction according to the axis of the top-blowing spray gun or the position of the side-blowing tuyere; establishing a radial one-dimensional or two-dimensional heat conduction equivalent model of the furnace lining, the buffer layer, the cooling wall and the furnace shell, and calculating temperature distribution at a key interface between the furnace shell and the furnace lining; establishing a calculation model of the equivalent thermal stress of each area of the furnace shell, and evaluating the equivalent thermal stress value and the safety margin of each control area; and establishing a multivariable feedback-feedforward control or model prediction control strategy, and dynamically matching the thermal load and the cooling capacity of each sub-region. According to the invention, real-time calculation and monitoring of equivalent thermal stress of key parts of the furnace shell and the furnace lining and dynamic reduction and preventive control of thermal stress of the furnace body are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of heavy non-ferrous pyrometallurgy and process equipment, and particularly relates to a method and device for regulating thermal stress of a non-ferrous smelting furnace body, and is particularly applied to a method and device for reducing and actively regulating thermal stress of a furnace body of a large-scale non-ferrous smelting furnace (including a top-blown smelting furnace, a side-blown smelting furnace, a bottom-blown furnace and the like) of copper, lead, nickel and the like, and particularly relates to a comprehensive technical scheme of flexible design of a furnace body structure, optimization of thermal expansion constraints of a furnace shell-furnace lining-cooling component and deep coupling of online prediction control of heat flow-temperature-stress. BACKGROUND With the development of heavy non-ferrous smelting towards large-scale, continuous and high-strength, the single-furnace processing capacity of a typical top-blown / side-blown smelting furnace is continuously improved, the hearth size is increased, the smelting pool is deeper, the flue gas volume and the unit volume heat load are significantly increased. Accompanied by this, the thermal and mechanical environment of the furnace body is more severe.

[0002] The local heat flux density in the high-temperature region is too large, the temperature difference between the inside and outside of the furnace lining and the radial temperature gradient are sharply increased, which leads to a large thermal expansion mismatch between the furnace lining and the furnace shell, and a thermal stress concentration is easily formed. The cooling component is often fixed with the steel furnace shell through rigid welding or bolts, and a large constraint thermal stress is generated due to the thermal expansion constraints, and failure problems such as weld cracking, cooling water leakage, cooling wall loosening and falling off, local furnace shell erosion and perforation often occur. The overall rigidity of the large-scale furnace body is high, and the constraints are strong, and the furnace shell has insufficient length and ring expansion freedom. When the temperature field in the furnace changes unevenly in space and time, a complex multi-field coupling constraint system is formed among the furnace shell, the furnace lining and the cooling component, which leads to a serious concentration of the thermal stress field, and has become one of the bottlenecks restricting the enlargement of the furnace body and the high-strength operation.

[0003] At present, the operation regulation of the furnace mainly depends on artificial experience, and the cooling water flow or blowing intensity is roughly adjusted according to a small amount of furnace shell temperature measurement points and cooling water inlet and outlet temperature information, which has obvious hysteresis and passivity. In this way, the heat flow distribution and the lining temperature field evolution process of each part of the furnace body cannot be accurately identified, and there is also a lack of a coordinated control strategy based on the heat load distribution and the furnace body thermal stress prediction results. Therefore, it is difficult to dynamically match the cooling capacity with the heat load in the furnace in a timely and accurate manner, and it is even more difficult to actively reduce and prevent the thermal stress of the furnace body. In addition, the existing design ignores the elastic, plastic and creep response of the furnace shell and the cooling structure under thermal load, and lacks an integrated scheme combining the flexible design of the furnace body structure and the active control of the thermal stress. In summary, an integrated technical scheme is urgently needed, which combines the layered flexible connection of the furnace body structure, the heat release guiding component, the partition cooling and the adjustable heat preservation structure with the online modeling of the furnace body heat flow-temperature-stress and the deep coupling of the multi-variable control system, to realize the thermal stress reduction and safe and stable operation of the large-scale smelting furnace under high-strength conditions.

[0004] Prior art 1, Chinese Patent Application No. 202510997182.2, relates to the field of monitoring and control technology, and particularly to a method and system for controlling the excess air coefficient of a coke oven based on real-time monitoring. This includes: acquiring coke oven equipment data and thermal stress distribution through sensors, obtaining sequence data of the excess air coefficient changing over time, and performing frequency domain analysis to determine a periodic model of the excess air coefficient. Based on this periodic model and real-time data, the future excess air coefficient sequence is predicted. When the prediction result is outside the reference range, the oven body is divided into multiple regions according to the real-time thermal stress distribution within the oven, and the distance between each region and the air inlet and the corresponding air supply component are calculated. The air supply rate is adjusted according to these parameters. After adjustment, the thermal stress distribution and excess air coefficient sequence data are reacquired to determine whether the air supply meets the requirements. If not, a corresponding adjustment strategy is obtained. Although this method can dynamically optimize the air supply of the coke oven, improve combustion stability, and ensure coke production quality, the concentration of thermal stress in the oven body leads to severe structural damage.

[0005] Prior art two, Chinese patent application number: 202510377374.3, describes a multi-physics coupling method for the smelting process of a nickel-iron submerged arc furnace. This method involves establishing a nickel-iron submerged arc furnace model, importing it into ICEM software for mesh generation, and finally importing the mesh into FLUENT. Based on Maxwell's equations and Ohm's law, and combined with user-defined functions (UDFs), electrothermal conversion, electromagnetic induction, and multiphase flow heat and mass transfer algorithms are compiled to establish a mathematical analysis model of the mutual coupling of multi-physics fields, multiphase flow, and furnace thermal stress in submerged arc furnace smelting. This model, combined with radiation models, turbulence models, multiphase flow models, and static structural models, reveals the heat and mass transfer mechanisms between the electric arc, molten pool, and furnace body, explores the influence mechanism of furnace structure and multi-physics fields on furnace temperature distribution, and clarifies the interaction mechanism between furnace temperature and thermal stress to predict the location and amount of furnace deformation. However, it lacks integrated online control of heat flow and stress.

[0006] Prior art three, Chinese patent application number: 202411882367.0, relates to an integral microwave-assisted additive manufacturing device and method, including a microwave high-temperature cavity, a microwave leak-proof outer cavity, microwave elements, a high-temperature thermocouple, a high-temperature support mechanism, and a servo drive mechanism. The microwave auxiliary device is fixed on a support frame, and the servo drive mechanism drives the forming substrate to move synchronously through the high-temperature support mechanism. It enables the additively manufactured component to autonomously absorb microwaves at the high-temperature forming state, converting microwave energy into heat energy, achieving rapid heating of the material itself. Simultaneously, under the synergistic effect of microwave-coupled external heat sources, it achieves synchronous preheating and slow cooling of the material's interior and exterior, reducing thermal stress during the forming process and effectively inhibiting material cracking. Although controlling the microwave power to regulate the heating temperature and rate allows for on-demand preparation of the material's microstructure; and the microwave plasma thermal effect and electric field enhancement effect during microwave heating can promote the densification of the formed component and significantly improve the overall performance of the material; however, the low precision matching between the melting furnace's heat load and cooling capacity leads to a reduced furnace life.

[0007] Currently, existing technologies 1, 2, and 3 suffer from problems such as severe structural damage due to concentrated thermal stress in the furnace body, lack of integrated online control of heat flow and stress, and low precision matching between the heat load and cooling capacity of the smelting furnace. To address these issues, this invention provides a method and apparatus for controlling thermal stress in a non-ferrous metal molten pool smelting furnace. Summary of the Invention

[0008] The main objective of this invention is to provide a method and apparatus for regulating the thermal stress of a non-ferrous metal molten pool smelting furnace body, in order to solve the problems in the prior art where the concentration of thermal stress in the furnace body leads to severe structural damage, lacks integrated online control of heat flow and stress, and has low precision matching between the smelting furnace's heat load and cooling capacity.

[0009] To achieve the above objectives, the present invention provides the following technical solution: A method for controlling the thermal stress of a non-ferrous metal molten pool smelting furnace body, comprising the following steps: Establish a radial one-dimensional or two-dimensional equivalent thermal conduction model of furnace lining-buffer layer-cooling wall-furnace shell, and calculate the temperature distribution at the key interface between the furnace shell and the furnace lining; establish a calculation model of equivalent thermal stress in each zone of the furnace shell, and evaluate the equivalent thermal stress value and safety margin of each control zone. Establish a multivariable feedback-feedforward control or model predictive control strategy to dynamically match the heat load and cooling capacity of each sub-zone; based on the control results of the predictive control strategy, predict the life of the molten pool furnace, and issue early warnings based on the prediction results.

[0010] As a further improvement of the present invention, the process of evaluating the equivalent thermal stress value and safety margin of each control zone includes the following steps: Using monitoring data such as inlet and outlet temperatures and flow rates of cooling water in each region, the average heat flux density transmitted from the corresponding zone is calculated; a radial one-dimensional or two-dimensional thermal conductivity equivalent model of furnace lining-buffer layer-cooling wall-furnace shell is established to calculate the temperature distribution at the key interface between the furnace shell and the furnace lining. The furnace lining-heat buffer layer-cooling wall-furnace shell is approximated as a multi-layer flat plate or multi-layer cylindrical structure. Assuming steady-state heat conduction is achieved in the radial direction, the total thermal resistance between each layer can be calculated using the equivalent thermal resistance. The average temperature of the cooling water sidewall can be approximated by the average of the inlet and outlet water temperatures. Based on the total thermal resistance, the equivalent thermal resistance, and the average inlet and outlet water temperatures, the hot surface temperature of the inner surface of the furnace lining in each region is estimated; based on the one-dimensional thermal conductivity relationship between the inner and outer surfaces of the furnace shell, the temperature difference of the furnace shell section is obtained; and based on the temperature field information, thermal stress calculations and safety assessments are performed.

[0011] As a further improvement to the present invention, the first There are several cooling zones, and the mass flow rate of the cooling water in each zone is obtained from measurements. The inlet temperature is The outlet temperature is The effective heat exchange area corresponding to the cooling zone is Based on the law of conservation of energy, calculate the average heat flux density of the cooling zone: in, The specific heat capacity of the cooling water at constant pressure is used to convert the measured cooling water parameters into the heat flux density transferred from the furnace body to each zone. The furnace lining-heat buffer layer-cooling wall-furnace shell is approximated as a multi-layered flat plate or multi-layered cylindrical structure, achieving steady-state heat conduction in the radial or one-dimensional direction. The inner surface temperature of the furnace lining is... The average temperature of the cooling water sidewall is The total thermal resistance between all layers can be expressed as the equivalent thermal resistance: in, For the first The thickness of the layer material, Its thermal conductivity, Let be the number of layers; neglecting radiation and convection, the radial temperature difference between the hot surface of the furnace lining and the cooling water wall surface satisfies: The average temperature of the cooling water sidewall can be approximated by the average of the inlet and outlet water temperatures: Online estimation of the hot surface temperature of the inner surface of the furnace lining in each region Based on the one-dimensional thermal conductivity relationship between the inner and outer surfaces of the furnace shell, the temperature difference of the furnace shell cross-section is obtained. : in, and The furnace shell thickness and the thermal conductivity of the furnace shell steel are respectively used to obtain a method for real-time calculation of the furnace lining hot surface temperature and the furnace shell cross-section temperature difference in each cooling zone based on monitoring data.

[0012] As a further improvement of the present invention, for the condition of unsteady-state effect, a one-dimensional unsteady-state heat conduction equation is established: In the formula These are the density, specific heat, and thermal conductivity of the layered material, respectively. For the heat source term; by combining offline numerical solution with online simplified model parameter identification, the behavior of complex PDEs is compressed into equivalent parameters of the form; The control system collects cooling water parameters and temperature signals from each cooling zone, and identifies the evolution of furnace heat flow and temperature field online, specifically including: calculating the real-time heat flux density transmitted from each zone. Estimate the temperature distribution of the inner surface of the furnace lining and the cross-sectional temperature of the furnace shell in each zone; perform online correction of the model parameters based on the measured values ​​of the furnace shell surface temperature and strain; dynamically track the heat load distribution and temperature gradient changes inside the furnace body through online identification; approximate a certain control zone of the furnace shell as a plate-like component under plane strain; when the thermal expansion of the control zone is constrained by the surrounding structure, its equivalent thermal stress is estimated according to the linear elastic thermal stress formula as follows: in, The elastic modulus of the furnace shell steel. The coefficient of linear expansion is 1 / 3. Poisson's ratio, This refers to the temperature difference or equivalent temperature gradient between the inner and outer surfaces of the furnace shell.

[0013] As a further improvement of the present invention, for regions with complex stress states, equivalent von Mises stress is adopted: It is the normal stress generated by the constraint of a non-uniform temperature field; It is shear stress; or With the allowable stress of the material The ratio is defined as a safety margin or safety indicator: in, This refers to the allowable stress value of the furnace shell material after considering the effects of fatigue and creep; after obtaining the temperature field information, thermal stress calculation and safety assessment are performed, including: calculating the equivalent thermal stress in each zone. ; Calculate the thermal stress safety index for each zone and with a pre-set security threshold Corresponding to the allowable stress Compare; if one or more partitions are found to be... The exposed area is in a state of excessive thermal stress or high risk; if all areas If all values ​​are within the safety threshold, the current control strategy will be maintained.

[0014] As a further improvement of the present invention, the entire furnace body is regarded as a dynamic thermal-structural system composed of multiple coupled zones; by linearizing the heat flow-temperature-stress relationship, the temperature, heat flow, and equivalent stress state variables of all zones are combined into a state vector. The control vector is composed of cooling water flow rate, insulation opening degree, jetting intensity, and airflow distribution execution quantity. This involves perturbations in material quantity, grade, and fuel quantity. Establish a linearized or piecewise linearized state-space model: Wherein, the state vector Includes furnace shell temperature, heat flux density, and equivalent thermal stress state parameters for each zone; control input vector. This includes the cooling water flow rate, adjustable insulation plate opening, spray intensity, and distributed execution variables for each zone; disturbance vector. Represents external interference factors; output vector Measurable quantities, including temperature and stress safety indicators for each zone. The overall goal of control is to create a vector composed of stress safety indices from each zone. Controlled within the physically permissible range, while maintaining the reaction intensity and thermal efficiency in the furnace: A represents the state transition matrix; B represents the control input matrix; E represents the disturbance input matrix; C represents the output matrix; y(k) represents the output vector, which represents the set of physical quantities that can be directly or indirectly obtained by sensors at time k.

[0015] As a further improvement to this invention, based on the state-space model, optimization control strategies such as model predictive control are designed, considering a length of... In the prediction time domain, the desired stress index vector is defined. and control reference values Select a positive definite weight matrix and Construct a multi-objective performance index function : In the formula, , The weight matrix is ​​minimized through online optimization. This allows for the acquisition of the optimal control increment at the current moment, enabling predictive reduction of thermal stress in multiple zones of the furnace body; performance indicators The weighted quadratic sum of the cumulative predicted stress deviation and control deviation in the time domain forms the mathematical basis for implementing the model predictive control strategy. This is achieved by minimizing... The optimal control input sequence is obtained by solving for the control input sequence, which reduces the thermal stress level in each region while satisfying the constraints.

[0016] As a further improvement to the present invention, the stress safety index of each zone is... Long-term statistical analysis was conducted; a cumulative damage factor for each region was defined and calculated using a criterion similar to Miner's linear cumulative damage criterion. : in, For the first The duration of each heat load cycle To be at stress amplitude The lifespan at which material fatigue failure occurs; the cumulative damage factor reflects the fatigue wear of the furnace shell structure under various thermal stress cycles; when a certain area... Approaching or exceeding the warning threshold When this occurs, it indicates that the area is nearing the end of its fatigue life, and a maintenance alarm and recommendation will be issued.

[0017] As a further improvement of the present invention, it also includes dividing the furnace shell along the length of the furnace into areas such as the feeding end area, the middle high heat load area, the copper or lead tapping area, and the nickel tapping end area, and dividing the furnace along the width of the furnace according to the axis of the top blowing lance or the position of the side blowing vent; monitoring the inlet and outlet temperatures and flow rates of the cooling water in each area, and calculating the average heat flux density of the corresponding zone based on the monitoring data.

[0018] As a further improvement of the present invention, the process of calculating the average heat flux density of the corresponding zone based on monitoring data includes the following steps: Based on the inlet temperature, outlet temperature and volumetric flow rate of the cooling water monitored in each zone, and combined with the specific heat capacity and density parameters of water, the actual heat power carried away by the cooling water in that zone per unit time is calculated; the heat power value is divided by the effective heat transfer area of ​​the inner surface of the furnace shell in the radial direction of the corresponding zone to obtain the preliminary value of the heat flux density of the zone based on the heat absorbed by the cooling water. By comparing the difference between the preliminary heat flux density value and the reference heat flux density value obtained by inversion calculation through the furnace lining-shell temperature measurement point during a known stable period of furnace heat load in the same zone, the zone heat transfer efficiency coefficient calibrated based on historical steady-state conditions is obtained through iterative fitting; the preliminary heat flux density value is divided by the zone heat transfer efficiency coefficient to obtain the corrected instantaneous heat flux density of the zone. Multiple instantaneous heat flux density samples continuously collected within a control cycle are time-series aligned and filtered for smoothing to remove singularities caused by measurement noise. The processed instantaneous heat flux density sequence is then arithmetically averaged within a monitoring time window to obtain the time-averaged heat flux density used to characterize the heat load level of the zone under the current operating conditions.

[0019] To achieve the above objectives, the present invention also provides the following technical solution: A thermal stress control device for a non-ferrous metal molten pool smelting furnace body is applied to the aforementioned thermal stress control method for the non-ferrous metal molten pool smelting furnace body. The thermal stress control device for the non-ferrous metal molten pool smelting furnace body includes: a furnace shell, a furnace lining, cooling components, flexible connectors, a thermal buffer layer, an adjustable insulation structure, a sensor, a control unit, a cooling wall, a sliding connection assembly, corrugated gaskets, a first region, a second region, a third region, and a fourth region. The furnace shell is divided into several areas along its length: the feeding end area, the middle high heat load area, and the copper or lead / nickel tapping end area; along its height: the molten pool area, the splash zone area, and the upper flue area; and along its width: the areas are divided according to the axis of the top-blown lance or the position of the side-blown duct; flexible connectors are installed at the connection between each cooling component and the furnace shell; a heat buffer layer is installed on the side of the cooling component closest to the furnace lining; and sensors are arranged in each control area, with the sensors transmitting data wirelessly to the control unit. A sliding connection assembly is provided on the furnace shell, and the sliding connection assembly is connected to the cooling wall; corrugated gaskets are provided on the inner side of the cooling wall and the furnace lining; The furnace body is divided into zones, with the furnace shell, furnace lining, and cooling components divided into several thermo-mechanical coupled control zones; namely, the first zone, the second zone, the third zone, and the fourth zone.

[0020] To achieve the above objectives, the present invention also provides the following technical solution: An electronic device includes a processor and a memory coupled to the processor, the memory storing program instructions executable by the processor; when the processor executes the program instructions stored in the memory, it implements the above-described method for controlling the thermal stress of a non-ferrous metal molten pool furnace body.

[0021] To achieve the above objectives, the present invention also provides the following technical solution: A storage medium storing program instructions, which, when executed by a processor, implement the above-described method for controlling the thermal stress of a non-ferrous metal molten pool furnace.

[0022] This invention proposes a method and device for controlling thermal stress in the furnace body of a non-ferrous metal molten pool furnace. The system combines a zoned flexible structure with a thermal stress release device, an integrated online prediction model for furnace heat flow, temperature, and stress, and a multi-actuator collaborative active control system and algorithm. This allows for the rational guidance and release of thermal expansion between the furnace shell, lining, and cooling components, reducing localized peak thermal stress in the furnace body. It enables real-time calculation and monitoring of equivalent thermal stress in key areas of the furnace shell and lining, and dynamic reduction and preventative control of thermal stress in the furnace body. This invention is applicable to various furnace types, including top-blown, side-blown, and bottom-blown furnaces. It can be used for overall design optimization of new furnaces, as well as for modular upgrades of existing furnaces' structures and control systems without altering the main furnace body. It has a wide range of applications and significant retrofitting value. Attached Figure Description

[0023] Figure 1 This is a schematic flowchart of one embodiment of the method for controlling thermal stress in a non-ferrous metal molten pool smelting furnace body according to the present invention. Figure 2 This is a schematic diagram of the furnace body heat flow-temperature-stress online prediction and control system framework of an embodiment of the furnace body thermal stress control method of the non-ferrous metal molten pool smelting furnace of the present invention. Figure 3 This is a schematic diagram of the steps in an embodiment of the method for controlling thermal stress in a non-ferrous metal molten pool furnace according to the present invention, which calculates the average heat flux density transmitted from the corresponding zone based on monitoring data. Figure 4 This is a schematic diagram illustrating the steps of evaluating the equivalent thermal stress values ​​and safety margins of each control zone in an embodiment of the non-ferrous metal molten pool smelting furnace thermal stress control method of the present invention. Figure 5 This is a flowchart of a furnace body thermal stress reduction and active control method according to an embodiment of the non-ferrous metal molten pool smelting furnace thermal stress control method of the present invention. Figure 6 This is a schematic diagram of the steps for early warning based on prediction results in one embodiment of the method for controlling thermal stress in a non-ferrous metal molten pool furnace body according to the present invention. Figure 7 This is a schematic diagram of the overall structure of the furnace body thermal stress reduction and control device in a top-blown molten pool smelting furnace, according to an embodiment of the present invention. Figure 8 This is a partial cross-sectional schematic diagram of the layered structure of the furnace shell, furnace lining, and cooling wall, as well as the flexible connecting parts, of an embodiment of the thermal stress control device for a non-ferrous metal molten pool smelting furnace of the present invention. Figure 9 This is a schematic diagram of the furnace body zoned cooling and adjustable heat preservation structure of an embodiment of the furnace body thermal stress control device for non-ferrous metal molten pool smelting furnace of the present invention. Figure 10 This is a schematic diagram of the structure of an embodiment of the electronic device of the present invention; Figure 11 This is a schematic diagram of the structure of a storage medium according to an embodiment of the present invention; Reference numerals: 1. Furnace shell; 2. Furnace lining; 3. Cooling component; 4. Flexible connector; 5. Thermal buffer layer; 6. Adjustable insulation structure; 7. Sensor; 8. Control unit; 9. Cooling wall; 10. Sliding connection assembly; 11. Corrugated gasket; 12. First region; 13. Second region; 14. Third region; 15. Fourth region; 16. Electronic equipment; 161. Processor; 162. Memory; 17. Storage medium; 171. Program instructions. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0025] The terms "first," "second," and "third" in this invention are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of those features. In the description of this invention, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this invention are only used to explain the relative positional relationships and movements between components in a specific orientation (as shown in the figures). If the specific orientation changes, the directional indication changes accordingly. Furthermore, the terms "including" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0026] References to embodiments herein mean that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0027] like Figure 1 As shown, this embodiment provides an example of a method for controlling the thermal stress of a non-ferrous metal molten pool furnace body. In this embodiment, the method for controlling the thermal stress of a non-ferrous metal molten pool furnace body specifically includes the following steps: Step S1: Divide the furnace shell along the length of the furnace into areas such as the feeding end area, the middle high heat load area, the copper or lead tapping area, and the nickel tapping end area. Divide the furnace along the width of the furnace according to the axis of the top blowing lance or the position of the side blowing vent. Monitor the temperature and flow rate of the cooling water inlet and outlet of each area, and calculate the average heat flux density of the corresponding zone based on the monitoring data. Step S2: Establish a radial one-dimensional or two-dimensional equivalent thermal conductivity model of furnace lining-buffer layer-cooling wall-furnace shell, calculate the temperature distribution at the key interface between furnace shell and furnace lining; establish a calculation model of equivalent thermal stress in each zone of furnace shell, and evaluate the equivalent thermal stress value and safety margin of each control zone. Step S3: Establish a multivariable feedback-feedforward control or model predictive control strategy to dynamically match the heat load and cooling capacity of each sub-region; based on the control results of the predictive control strategy, predict the lifespan of the molten pool furnace and issue early warnings based on the prediction results.

[0028] Preferably, in this embodiment, for areas with high temperature and stress, cooling is enhanced by increasing the cooling water flow rate or increasing the water-side flow velocity in that area without reducing the reaction intensity inside the furnace, thereby increasing the heat extraction rate and reducing the furnace shell temperature at that location. This rapidly reduces the level of thermal stress; conversely, for areas where excessive cooling leads to excessively low furnace lining temperatures and a risk of thermal cracking, the cooling water intensity can be appropriately reduced, or the opening of the adjustable insulation structure 6 can be adjusted to increase the insulation effect at that location and reduce the peak temperature gradient. For adjusting the cooling water flow rate, a simple local proportional control principle can be adopted, for example: in For the region Stress feedback gain, The desired stress index is determined by the control law, which adjusts the cooling flow rate based on the current stress deviation to achieve rapid local cooling control. In top-blown or side-blown molten pool furnaces, the position of the lance and the oxygen / fuel injection intensity directly affect the local heat flow distribution within the furnace. If the thermal stress in a certain area remains high for an extended period, measures can be taken to coordinately adjust the injection regime: appropriately fine-tuning the pitch angle, rotation angle, or oxygen / fuel supply per lance of the top-blown lance can slightly shift the position of the flame or high-speed jet to an area with stronger refractory capacity. For side-blown tuyeres, the oxygen enrichment or fuel injection rate of each tuyer can be adjusted in zones to guide some of the heat load to areas with lower heat loads. Simultaneously, the feeding and distribution of the furnace charge can be optimized to balance the heat release intensity throughout the molten pool. Thus, while ensuring the overall smelting intensity, the excessively high heat load in specific areas can be alleviated, reducing the thermal stress borne by the furnace lining and shell in those areas. During furnace preheating, routine shutdown cooling, and emergency conditions, the control system adjusts the overall furnace heating or cooling rate based on model-predicted furnace shell temperature and stress change rate to avoid excessive thermal shock. For example, during the uniform heating phase, the average heating rate of the furnace shell can be limited. Not exceeding a certain upper limit When the model predicts that the thermal stress in a certain area will exceed the allowable value, the heating rate is reduced in advance by decreasing the fuel input or uniformly increasing the cooling water flow rate to prevent stress overshoot. Similarly, the cooling rate is controlled during emergency cooling to prevent a sudden increase in thermal stress. By constraining the rate of heating and cooling, the stress in the furnace body under abnormal operating conditions can be prevented and controlled.

[0029] In summary, this embodiment selects the equivalent thermal stress index and furnace shell temperature of each zone as the main control targets, and uses cooling water zone flow rate, cooling water inlet and outlet temperature difference, adjustable insulation board opening, injection intensity, and injection distribution as control variables. A multivariate feedback-feedforward control or model predictive control strategy is adopted to achieve dynamic matching of heat load and cooling capacity in each zone, thereby actively reducing peak thermal stress and avoiding thermal shock and fatigue damage caused by local overheating or overcooling. For areas determined to have a risk of exceeding thermal stress limits, this invention employs a hierarchical, multi-actuator collaborative control strategy for stress reduction (see appendix for details). Figure 2 Through the design of flexible connectors, thermal buffer layers, and release grooves, the thermal expansion differences between the furnace shell, furnace lining, and cooling components are effectively released, allowing thermal expansion to have a path and enabling thermal expansion displacement to be released along a predetermined path; reducing the peak and gradient of thermal stress, achieving structural response characteristics of priority displacement release and delayed stress generation, playing a role in peak shaving and valley filling, and alleviating thermal stress concentration.

[0030] Furthermore, such as Figure 3 As shown, step S1, which calculates the average heat flux density of the corresponding zone based on monitoring data, specifically includes the following steps: Step S11: Based on the inlet temperature, outlet temperature and volumetric flow rate of the cooling water obtained from the monitoring of each zone, and combined with the specific heat capacity and density parameters of water, calculate the actual heat power carried away by the cooling water in the zone per unit time; divide the heat power value by the effective heat transfer area of ​​the inner surface of the furnace shell in the radial direction of the corresponding zone to obtain the preliminary value of the heat flux density of the zone based on the heat absorption of the cooling water. Step S12: By comparing the difference between the preliminary heat flux density value and the reference heat flux density value obtained by inversion calculation through the furnace lining-shell temperature measurement point during the known stable period of the furnace heat load in the same zone, the zone heat transfer efficiency coefficient calibrated based on historical steady-state conditions is obtained through iterative fitting; the preliminary heat flux density value is divided by the zone heat transfer efficiency coefficient to obtain the corrected instantaneous heat flux density of the zone. Step S13: Perform time-series alignment and filtering smoothing on multiple instantaneous heat flux density samples continuously collected within a control cycle to remove singularities caused by measurement noise; perform arithmetic averaging on the processed instantaneous heat flux density sequence within a monitoring time window to obtain the time-averaged heat flux density used to characterize the heat load level of the zone under the current operating conditions.

[0031] Preferably, in this embodiment, the preliminary value of the heat flux density of each zone is obtained through cooling water heat balance calculation, and then corrected by combining it with the heat transfer efficiency coefficient calibrated under historical steady-state conditions. This effectively eliminates systematic errors caused by differences in furnace lining structure, non-uniformity of heat transfer paths, and measurement system deviations, improving the physical consistency of the heat flux density calculation. Time-series filtering and moving average processing are applied to the corrected instantaneous heat flux density to suppress the influence of random measurement noise and instantaneous disturbances, extracting characteristic quantities reflecting the stable trend of the zone's heat load. The final output time-averaged heat flux density is both real-time and representative, providing a reliable quantitative basis for furnace thermal state monitoring and dynamic control of the cooling system. Furthermore, through the calibration and iterative updating of the zone's heat transfer efficiency coefficient, the ability to adaptively correct the furnace shell heat transfer process is achieved.

[0032] Furthermore, the process of obtaining the zoned heat transfer efficiency coefficient based on historical steady-state operating conditions through iterative fitting in step S12 specifically includes the following steps: Step S121: Collect the data set recorded by the target partition under multiple historical steady-state conditions, including the preliminary value of heat flux density calculated at each steady-state condition moment, and the reference value of heat flux density calculated in reverse based on the radial heat transfer model at the same moment through the network of temperature measuring points deployed in the furnace lining and furnace shell of the partition. Step S122: Construct an initial nominal value for the heat transfer efficiency coefficient of each zone, divide the preliminary value of the heat flux density under each steady-state condition by the nominal value to obtain a set of calculated heat flux density values; compare the calculated heat flux density values ​​with the corresponding heat flux density reference values ​​one by one, and calculate the overall deviation measure between all data pairs. Step S123: Initiate an iterative optimization process to automatically adjust the value of the partition heat transfer efficiency coefficient with the goal of minimizing the overall deviation metric. After each adjustment, the overall deviation metric is recalculated until the metric meets the preset convergence threshold condition. The obtained partition heat transfer efficiency coefficient value is determined as the final heat transfer efficiency coefficient of the partition based on historical steady-state operating conditions.

[0033] Preferably, this embodiment constructs a data set by collecting the preliminary calculated heat flux density values ​​under historical steady-state conditions and the reference heat flux density values ​​obtained by temperature measurement network inversion, providing a data basis for the calibration of the heat transfer efficiency coefficient; and associates the regional heat transfer characteristics with the measured temperature field to form a mapping framework from calculated values ​​to actual heat transfer state. Starting with an initial nominal value, the system calculates the deviation between the calculated heat flux density value and the reference value by comparing them pairwise. It then initiates iterative optimization based on the overall deviation metric, dynamically converging the heat transfer efficiency coefficient to its optimal value. The system compresses the heat transfer characteristics implicit in historical steady-state data into a single correction coefficient, automatically compensating for errors caused by model simplification in online calculations. By minimizing the overall deviation between the calculated and reference values, the initial heat flux density value, after correction by the heat transfer efficiency coefficient, more accurately reflects the actual heat transfer intensity. The calibration process reduces calculation errors caused by differences in partitioned structures, uncertainties in boundary conditions, or measurement noise, providing a more stable input benchmark for subsequent online estimation of temperature and stress fields. The iterative optimization process terminates with a convergence threshold, achieving automatic closed-loop parameter calibration. The system allows for autonomous coefficient calibration driven by historical data, eliminating the need for manual adjustments and enhancing the model's adaptability to different operating conditions and historical datasets. This provides a standardized method for model maintenance during long-term operation. The heat transfer efficiency coefficient, as a key correction parameter for heat flux density calculation, directly affects the estimation accuracy of the furnace lining hot surface temperature and furnace shell temperature gradient. The coefficients obtained by fitting historical data effectively bridge the theoretical heat transfer model with the actual equipment condition, providing verified input conditions for subsequent thermal stress safety assessment, thus forming a progressive accuracy guarantee across the entire chain from data acquisition to safety judgment.

[0034] Furthermore, the process of calculating the heat flux density reference value based on the radial heat transfer model in step S121 specifically includes the following steps: Step S1211: Call the network of temperature measurement points deployed at specific radial positions inside the partitioned furnace lining and furnace shell to obtain a set of temperature measurement values ​​synchronously collected under steady-state conditions, forming a temperature sequence distributed radially. Step S1212: Input the temperature sequence into the pre-established radial one-dimensional thermal conductivity equivalent model of furnace lining-buffer layer-cooling wall-furnace shell; calculate the equivalent thermal resistance of the material layer between adjacent temperature measurement points using the defined thermal conductivity characteristics and geometric thickness parameters of each layer; according to the heat transfer law followed by the radial thermal conductivity equivalent model, divide the temperature difference between adjacent temperature measurement points by the corresponding equivalent thermal resistance to calculate the local heat flux density through the interface of the material layer. Step S1213: Integrate and verify the multiple local heat flux density results calculated along the radial path, eliminate unreliable calculation results caused by abnormal temperature measurement points, and perform weighted averaging on the remaining results; determine the heat flux density value after weighted averaging as the reference value of heat flux density through the key interface of furnace lining-furnace shell under the steady-state operating condition.

[0035] Preferably, this embodiment uses a network of temperature measuring points deployed at specific radial positions inside the furnace lining and furnace shell to synchronously collect temperature data under steady-state conditions, forming a continuously distributed temperature sequence along the radial direction. This provides a reliable and synchronous measured temperature field basis for subsequent heat transfer analysis. The acquired temperature sequence is input into a pre-established radial one-dimensional thermal conductivity equivalent model of the furnace lining-buffer layer-cooling wall-furnace shell. Combining the known thermal conductivity characteristics and geometric thickness parameters of each layer, the equivalent thermal resistance between adjacent temperature measuring points is calculated. Based on the fundamental law of radial thermal conduction, the local heat flux density through each material interface is calculated layer by layer using the ratio of the temperature difference between adjacent measuring points to the corresponding equivalent thermal resistance, realizing the quantitative conversion from temperature measurement values ​​to heat flux density. The multiple local heat flux density results calculated along the radial path are integrated and verified, unreliable data caused by abnormal temperature measuring points are excluded, and the remaining valid results are weighted and averaged. The final determined heat flux density reference value can accurately characterize the overall heat transfer intensity through the key interface between the furnace lining and the furnace shell under steady-state conditions, providing key heat flux data support for furnace thermal state assessment, cooling system optimization, and safe operation.

[0036] Furthermore, such as Figure 4 As shown, the process of evaluating the equivalent thermal stress value and safety margin of each control zone in step S2 specifically includes the following steps: Step S21: Using monitoring data such as the inlet and outlet temperatures and flow rates of cooling water in each region, calculate the average heat flux density transmitted from the corresponding zone; establish a radial one-dimensional or two-dimensional equivalent thermal conductivity model of furnace lining-buffer layer-cooling wall-furnace shell, and calculate the temperature distribution at the key interface between the furnace shell and the furnace lining. Step S22: The furnace lining-heat buffer layer-cooling wall-furnace shell is approximated as a multi-layer flat plate or multi-layer cylindrical structure. Assuming steady-state heat conduction is achieved in the radial direction, the total thermal resistance between each layer can be calculated using the equivalent thermal resistance; the average temperature of the cooling water sidewall can be approximated by the average value of the inlet and outlet water temperatures. Step S23: Estimate the hot surface temperature of the inner surface of the furnace lining in each region based on the total thermal resistance, the available equivalent thermal resistance, and the average values ​​of the inlet and outlet water temperatures; obtain the temperature difference of the furnace shell section based on the one-dimensional thermal conductivity relationship between the inner and outer surfaces of the furnace shell section; and perform thermal stress calculation and safety assessment based on the temperature field information.

[0037] Preferably, in this embodiment, the first... There are several cooling zones, and the mass flow rate of the cooling water in each zone is obtained from measurements. The inlet temperature is The outlet temperature is The effective heat exchange area corresponding to this zone is According to the law of conservation of energy, the average heat flux density in this region can be calculated: in, By using the constant pressure specific heat capacity of cooling water, directly measurable cooling water parameters are converted into heat flux density transferred from the furnace body to each zone, realizing online mapping from measurable water measurements to invisible furnace body heat flux density. This is the basic input for temperature field and stress estimation. The furnace lining-heat buffer layer-cooling wall-furnace shell is approximated as a multi-layered flat plate or multi-layered cylindrical structure. Assuming steady-state heat conduction is achieved radially (one-dimensionally), the inner surface temperature of the furnace lining is... The average temperature of the cooling water sidewall is The total thermal resistance between all layers can be expressed as the equivalent thermal resistance: in, For the first The thickness of the layer material, Its thermal conductivity, Let be the number of layers; neglecting radiation and convection, the radial temperature difference between the hot surface of the furnace lining and the cooling water wall surface satisfies: The average temperature of the cooling water sidewall can be approximated by the average of the inlet and outlet water temperatures: Online estimation of the hot surface temperature of the inner surface of the furnace lining in each region Furthermore, based on the one-dimensional thermal conductivity relationship between the inner and outer surfaces of the furnace shell cross-section, the temperature difference of the furnace shell cross-section can be obtained. : in, and These represent the furnace shell thickness and the thermal conductivity of the furnace shell steel, respectively. Through the above steps, a method was obtained to calculate the temperature difference between the hot surface of the furnace lining and the cross-sectional temperature of the furnace shell in real time from monitoring data.

[0038] For operating conditions that require consideration of unsteady-state effects (such as temperature rise, furnace shutdown, or abnormal fluctuations), a one-dimensional unsteady-state heat conduction equation can be established: In the formula These are the density, specific heat, and thermal conductivity of the layered material, respectively. For the volumetric heat source term, the behavior of complex PDEs can be compressed into equivalent parameters of a certain form by combining offline numerical solutions with online simplified model parameter identification.

[0039] The control system operates at a certain cycle (e.g., every...) (Seconds) Collect cooling water parameters and temperature signals from each zone, and identify the evolution of furnace heat flow and temperature field online, specifically including: calculating the real-time heat flux density transmitted from each zone. Estimate the temperature distribution of the inner surface of the furnace lining and the cross-sectional temperature of the furnace shell in each zone; combine the measured values ​​of the furnace shell surface temperature and strain to perform online correction of the model parameters, improving the accuracy of the heat flow-temperature field model calculation; through the above online identification, the heat load distribution and temperature gradient changes inside the furnace can be dynamically tracked; a certain control zone of the furnace shell is approximated as a plate-like component under plane strain; when the thermal expansion of this region is constrained by the surrounding structure, its equivalent thermal stress can be estimated according to the linear elastic thermal stress formula: in, The elastic modulus of the furnace shell steel. The coefficient of linear expansion is 1 / 3. Poisson's ratio, The temperature difference (or equivalent temperature gradient) between the inner and outer surfaces of the furnace shell. For regions with more complex stress states, equivalent von Mises stress can be further employed: It is the normal stress generated by the constraint of a non-uniform temperature field, and is the main body of thermal stress; It is shear stress; Furthermore, to facilitate online monitoring and control, it is usually... or With the allowable stress of the material The ratio is defined as the safety margin: in, This refers to the allowable stress value of the furnace shell material after considering the effects of fatigue and creep. After obtaining the temperature field information, further thermal stress calculations and safety assessments are performed, including: calculating the equivalent thermal stress in each zone. ; Calculate the thermal stress safety index for each zone and with a pre-set security threshold Corresponding to the allowable stress Compare; if one or more partitions are found to be... This indicates that the area is in a state of excessive or high-risk thermal stress, requiring intervention and reduction through the control system; if all areas If all values ​​are within the safety threshold, the current control strategy will be maintained or only minor optimizations will be made to improve economic efficiency. This step allows for real-time assessment of the thermal stress state of various parts of the furnace body and timely determination of whether intervention control is necessary (see appendix for details).Figure 5 ).

[0040] In summary, this embodiment establishes an online prediction model for heat flow, temperature, and stress, and constructs an online calculation chain from water-side heat flow → furnace lining temperature → furnace shell temperature → thermal stress → safety indicators. This transforms the internal thermal stress field of the furnace body, which was originally difficult to measure in real time, into a monitoring indicator that can be calculated online. This realizes the transformation from the traditional temperature-centered active control mode to the thermal stress-centered active control mode, that is, the leap from temperature control to thermal stress control.

[0041] Furthermore, such as Figure 6 As shown, the process of issuing an early warning based on the prediction results in step S3 specifically includes the following steps: Step S31: Linearize the heat flux-temperature-stress relationship, and form a state vector from the state variables such as temperature, heat flux, and equivalent stress of all zones; form a control vector from the execution variables such as cooling water flow rate, insulation opening, injection intensity, and airflow distribution; and form a control vector from the disturbances such as material quantity, grade, and fuel quantity. ; Step S32: Establish a linearized or piecewise linearized state-space model, design optimization control strategies such as model predictive control, and select a positive definite weight matrix of appropriate dimension. and Construct a multi-objective performance index function By minimizing To obtain the optimal control input sequence; Step S33: Determine the stress safety index for each zone. Long-term statistical analysis was conducted to calculate the cumulative damage factor for each region. When a certain area Approaching or exceeding the warning threshold When this occurs, it indicates that the area is nearing the end of its fatigue life, and the system will issue a maintenance alarm and recommendations.

[0042] Preferably, in this embodiment, the entire furnace body is regarded as a dynamic thermal-structural system composed of multiple coupled zones; by linearizing the above-mentioned heat flow-temperature-stress relationship, the temperature, heat flow, and equivalent stress of all zones are combined into a state vector. The control vector is composed of actuators such as cooling water flow rate, insulation opening, injection intensity, and airflow distribution. This involves perturbations in material quantity, grade, and fuel quantity. Establish a linearized or piecewise linearized state-space model: Wherein, the state vector Includes state variables such as furnace shell temperature, heat flux density, and equivalent thermal stress in each zone; control input vector. Execution variables include cooling water flow rate in each zone, adjustable insulation plate opening, spray intensity and distribution, etc.; disturbance vector. This represents external interference factors, such as the quantity and grade of materials fed into the furnace, and fluctuations in fuel supply; the output vector... For measurability, including temperature and stress safety indicators for each zone. The overall objective of control is to create a vector composed of stress safety indices from each zone. The control is to minimize the impact within physically permissible limits while maintaining the reaction intensity and thermal efficiency within the furnace. A, B, E, C, and y(k) are the core matrices and vectors in the state-space model, with the following meanings: A represents the state transition matrix, describing the dynamic evolution of the system's internal state from the current time k to the next time k+1; matrix elements characterize the coupling strength and time constant between state variables, reflecting the physical laws of furnace thermal inertia, heat transfer, and stress transmission; B represents the control input matrix, establishing the influence of control variables u(k) (such as cooling water flow rate and insulation opening) on ​​state variables x(k); matrix elements quantify the adjustment capability and response speed of each actuator to the zoned thermal and stress states; E represents the disturbance input matrix, characterizing the interference path and intensity of external uncontrollable disturbances d(k) on the system state; the matrix incorporates random fluctuations in the production process into the dynamic model, improving the robustness of the control system to changes in operating conditions; C represents the output matrix, defining the system's measurable output y(k) and internal state x(k). The mapping relationship between them; since quantities that can be directly monitored, such as temperature and stress safety indicators, are usually only a subset or linear combination of state variables; to realize the conversion from full state to observed quantities; y(k) represents the output vector representing the set of physical quantities that can actually be obtained directly or indirectly by sensors at time k; Based on the state-space model described above, optimization control strategies such as model predictive control can be designed. Therefore, consider a model with a length of... In the prediction time domain, the desired stress index vector is defined. and control reference values Select a positive definite weight matrix of appropriate dimension. and Construct a multi-objective performance index function : In the formula , The weight matrix is ​​minimized through online optimization. This allows for the acquisition of the optimal control increment at the current moment, enabling predictive reduction of thermal stress in multiple zones of the furnace body. The aforementioned performance indicators... The weighted quadratic sum of the predicted stress deviation and control deviation within the time domain forms the mathematical basis for the model predictive control strategy implemented in this invention. This is achieved by minimizing... The optimal control input sequence is obtained by solving the problem, thereby minimizing the thermal stress level in each zone and maintaining the efficient operation of the furnace while satisfying the constraints. This optimization can be performed on a rolling basis in each control cycle, and constraints on control quantities and stress indicators can be added as needed to ensure control behavior and furnace safety. This embodiment also considers the cumulative effect of furnace thermal stress and life management, and sets stress safety indicators for each zone. Long-term statistical analysis was conducted. To assess the impact of thermal stress cycles on the lifespan of the furnace shell and cooling components during long-term operation, this invention employs a method similar to Miner's linear cumulative damage criterion, defining and calculating the cumulative damage factor for each region. : in, For the first The duration of each heat load cycle To be at stress amplitude The lifespan at which material fatigue failure occurs; the cumulative damage factor reflects the fatigue wear of the furnace shell structure under various thermal stress cycles; when a certain area... Approaching or exceeding the warning threshold When the system detects that the area is nearing the end of its fatigue life, it will issue a maintenance alarm and recommendations, suggesting that planned shutdown maintenance or replacement of relevant cooling modules, optimization of structural design, and other preventive measures are needed. Through the above-mentioned life monitoring and early warning management, the furnace structure can be transformed from passive failure to proactive maintenance, improving the safety and reliability of furnace operation.

[0043] In summary, under a unified optimization control objective, this embodiment coordinates and adjusts multiple actuators such as cooling water flow, injection process, and adjustable insulation structure to ensure the required reaction intensity in the high-temperature zone of the furnace while controlling the furnace shell and cooling components to prevent excessive thermal stress, thus achieving a balance between high-intensity smelting and a long-life furnace body.

[0044] This embodiment also provides an embodiment of a thermal stress control device for a non-ferrous metal molten pool smelting furnace body. In this embodiment, the thermal stress control device for a non-ferrous metal molten pool smelting furnace body is applied to the thermal stress control method for a non-ferrous metal molten pool smelting furnace body as described in the above embodiment. The thermal stress control device for a non-ferrous metal molten pool smelting furnace body includes a furnace shell 1, a furnace lining 2, a cooling component 3, a flexible connector 4, a thermal buffer layer 5, an adjustable insulation structure 6, a sensor 7, a control unit 8, a cooling wall 9, a sliding connection assembly 10, a corrugated gasket 11, a first region 12, a second region 13, a third region 14, and a fourth region 15. Among them, such as Figure 7As shown, the furnace shell 1 is divided into several areas along the length of the furnace, such as the feeding end area, the middle high heat load area, the copper or lead tapping area, and the nickel tapping end area; along the height, it is divided into the molten pool area, the splash zone area, and the upper flue area; along the width of the furnace, it is divided into areas according to the axis of the top blowing lance or the position of the side blowing vent; a flexible connector 4 is provided at the connection between each cooling component 3 and the furnace shell 1; a heat buffer layer 5 is provided on the side of the cooling component 3 near the furnace lining 2; and sensors 6 are arranged in each control area, and the sensors 6 transmit data wirelessly to the control unit 8. like Figure 8 As shown, a sliding connection assembly 10 is provided on the furnace shell 1, and a cooling wall 9 is connected to the sliding connection assembly; corrugated gaskets 11 are provided on the inner side of the cooling wall 9 and the furnace lining. like Figure 9 As shown, the furnace body is divided into several thermo-mechanical coupling control zones, including the furnace shell 1, furnace lining 2, and cooling components 3. For example, the zones are divided into the first zone 12, the second zone 13, the third zone 14, and the fourth zone 15.

[0045] Preferably, the furnace shell 1 is divided into several regions along its length, including the feeding end region, the central high heat load region, the copper or lead tapping region, and the nickel tapping end region; along its height, it is divided into the molten pool region, the splash zone region, and the upper flue region; and along its width, it is divided into regions according to the axis of the top-blown lance or the position of the side-blown duct. By combining these dimensions, the furnace body can be discretized into several thermo-mechanical coupled control unit regions. Independent monitoring and control are implemented for each area; flexible connectors 4 are installed at the connection between each cooling component 3 and the furnace shell 1 to buffer thermal stress. Specifically, an elongated hole fixing plate is installed on the outside of the cooling component, and it is connected to the furnace shell using elongated hole bolts, allowing a certain amount of sliding displacement along the main thermal expansion direction; corrugated metal gaskets or high-temperature elastic gaskets are placed between the contact surfaces of the cooling component and the furnace shell to buffer local rigid impacts and adapt to uneven thermal expansion; in addition, a combination of sliding supports and fixed supports is used between the furnace shell and the foundation, with the fixed supports defining the reference position of the furnace shell and the sliding supports allowing the furnace shell to expand freely along the length of the furnace; a thermal buffer layer 5 is set on the side of the cooling component 3 near the furnace lining 2. This buffer layer is composed of refractory castables or lightweight refractory bricks with low thermal conductivity and good thermal shock resistance, forming a gradient heat conduction path of high-temperature furnace lining-thermal buffer layer-cooling wall, slowing down the heat flow conduction rate from the furnace lining to the cooling wall. Simultaneously, several thermal stress relief grooves are opened along the circumference or vertical direction of the furnace shell, allowing local thermal expansion to be concentrated and released in a predetermined direction, reducing the constraint stiffness of the large overall structure. According to the furnace body's zonal flexible structure design, the furnace shell, furnace lining, and cooling components are divided into several thermo-mechanical coupled control zones. Necessary sensors are arranged in each control zone to form a temperature-strain monitoring network. For example, cooling water flow meters and cooling water inlet and outlet temperature sensors are installed to acquire heat flow-related data; surface temperature sensors and strain gauges or fiber optic grating sensors are arranged at key locations on the furnace shell to monitor the furnace shell temperature and strain. Through the above sensor arrangement, real-time monitoring of the temperature and stress state of each area of ​​the furnace body is achieved. Through this design, when the furnace body encounters rapid heating or drastic fluctuations in local heat flow, it will not immediately and completely restrict all thermal expansion to the structure, resulting in high stress. Instead, by allowing a certain degree of slippage, elastic deformation, and thermal buffer delay, it prioritizes the release of expansion displacement and delays stress formation, exhibiting a response characteristic of priority displacement release and delayed stress generation. This greatly alleviates the peak thermal stress of the furnace body during sudden temperature changes.

[0046] In summary, the furnace shell is divided into several thermo-mechanical control zones along its length, width, and height. Each zone is equipped with partitioned cooling components and flexible connectors. The cooling components are connected to the furnace shell via sliding or elastic connection assemblies, forming a limited constraint connection that allows for relative sliding displacement along the main thermal expansion direction. A thermal buffer layer and thermal stress relief grooves are installed between the furnace lining and the cooling wall, forming a multi-layered gradient thermal conduction structure of refractory material, insulation material, and cooling components. This reduces abrupt temperature gradients at the interfaces, releases thermal expansion strain, and minimizes thermal stress concentration.

[0047] in, like Figure 10 As shown, this embodiment provides an embodiment of an electronic device 16, which includes a processor 161 and a memory 162 coupled to the processor 161.

[0048] The memory 162 stores program instructions for implementing the thermal stress control method of the non-ferrous metal molten pool smelting furnace body in any of the above embodiments.

[0049] The processor 161 is used to execute program instructions stored in the memory 162 to lay out a method for controlling the thermal stress of the furnace body in a non-ferrous metal molten pool smelting furnace.

[0050] The processor 161 can also be referred to as a CPU (Central Processing Unit). The processor 161 may be an integrated circuit chip with signal processing capabilities. The processor 161 can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor.

[0051] Furthermore, Figure 11 This is a schematic diagram of the structure of a storage medium according to an embodiment of this application. The storage medium 17 of this embodiment stores program instructions 171 capable of implementing all the methods described above. These program instructions 171 can be stored in the storage medium in the form of a software product, including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, or terminal devices such as computers, servers, mobile phones, and tablets.

[0052] In the several embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0053] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units. The above are merely embodiments of the present invention and do not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

[0054] The specific embodiments of the invention have been described in detail above, but these are merely examples, and the invention is not limited to the specific embodiments described above. For those skilled in the art, any equivalent modifications or substitutions to the invention are also within the scope of this invention. Therefore, all equivalent transformations, modifications, and improvements made without departing from the spirit and principles of this invention should be included within the scope of this invention.

Claims

1. A method for controlling the thermal stress of a non-ferrous metal molten pool smelting furnace body, characterized in that, The non-ferrous metal bath smelting furnace body thermal stress regulation method comprises the following steps: A one-dimensional or two-dimensional radial heat conduction equivalent model of the furnace lining-buffer layer-cooling wall-furnace shell is established to calculate the temperature distribution at the key interface between the furnace shell and the furnace lining; a calculation model of the equivalent thermal stress of each region of the furnace shell is established to evaluate the equivalent thermal stress value and the safety margin of each control region; A multivariable feedback-forefeed control or model prediction control strategy is established to dynamically match the thermal load and cooling capacity of each sub-region; the service life of the bath smelting furnace is predicted according to the control results of the prediction control strategy, and a warning is given according to the prediction results.

2. The method of claim 1, wherein the method further comprises: The process of evaluating the equivalent thermal stress value and the safety margin of each control region comprises the following steps: ​ The average heat flux density of the corresponding sub-region is calculated by using the monitoring data such as the inlet and outlet temperatures and flow rates of the cooling water of each region; a one-dimensional or two-dimensional radial heat conduction equivalent model of the furnace lining-buffer layer-cooling wall-furnace shell is established to calculate the temperature distribution at the key interface between the furnace shell and the furnace lining; The furnace lining-thermal buffer layer-cooling wall-furnace shell is approximated as a multi-layered flat plate or a multi-layered cylinder structure, and it is assumed that the radial steady-state heat conduction is achieved, so that the total thermal resistance between each layer can be calculated as the equivalent thermal resistance; the average temperature of the cooling water side wall can be approximated as the average of the inlet and outlet water temperatures; The hot surface temperature of the inner surface of the furnace lining of each region is estimated according to the total thermal resistance equivalent thermal resistance and the average of the inlet and outlet water temperatures; the temperature difference of the cross section of the furnace shell is obtained according to the one-dimensional heat conduction relationship between the inner and outer surfaces of the cross section of the furnace shell; the thermal stress calculation and safety discrimination are performed according to the temperature field information.

3. The method of claim 2, wherein the method further comprises: For the There are several cooling zones, and the mass flow rate of the cooling water in each zone is obtained from measurements. Inlet temperature is The outlet temperature is The effective heat exchange area corresponding to the cooling zone is Based on the law of conservation of energy, calculate the average heat flux density of the cooling zone: in, The specific heat capacity of the cooling water at constant pressure is used to convert the measured cooling water parameters into the heat flux density transferred from the furnace body to each zone. The furnace lining-thermal buffer-cooling wall-furnace shell is approximated as a multi-layer flat plate or multi-layer cylinder structure, and the radial or one-dimensional steady-state heat conduction is reached, the furnace lining inner surface temperature is , the cooling water side wall average temperature is ; the total thermal resistance between each layer can be represented by the equivalent thermal resistance: wherein, is the thickness of the layer material, is its thermal conductivity, is the number of layers; when radiation and convection are ignored, the radial temperature difference between the hot surface of the furnace lining and the cooling water wall surface satisfies: The average temperature of the cooling water side wall can be approximated as the average of the inlet and outlet water temperatures: The online estimation of the hot surface temperature of the furnace lining inner surface of each region , according to the one-dimensional heat conduction relationship of the inner and outer surfaces of the furnace shell cross section, the temperature difference of the furnace shell cross section is obtained : wherein, and are the thickness of the furnace shell and the thermal conductivity of the furnace shell steel respectively; a method for real-time calculation of the hot surface temperature of each cooling partition furnace lining and the temperature difference of the furnace shell cross section from the monitoring data is obtained.

4. The method of claim 3, wherein the method further comprises: For the non-steady-state working condition, the one-dimensional non-steady-state heat conduction equation is established: wherein ρ, c, k are the density, specific heat and thermal conductivity of the layered material, respectively, is the volumetric heat source term; by combining off-line numerical solution with on-line simplified model parameter identification, the behavior of the complex PDE is compressed into the equivalent parameters of the form; The control system collects cooling water parameters and temperature signals of each cooling partition, and identifies the heat flow and temperature field evolution of the furnace body online, specifically including: calculating the real-time heat flux density of each zone ; estimating the hot surface temperature of the inner surface of each zone and the temperature distribution of the furnace shell cross section; combining the measured values of the furnace shell surface temperature and strain to correct the model parameters online; through online identification, dynamically tracking the heat load distribution and temperature gradient change inside the furnace body; regarding a certain control zone of the furnace shell as a plate-shaped member in a plane strain state; when the thermal expansion of the control area is constrained by the surrounding structure, its equivalent thermal stress is estimated according to the linear elastic thermal stress formula as follows: wherein, is the elastic modulus of the furnace shell steel material, is the linear expansion coefficient, is the Poisson's ratio, is the temperature difference between the inner and outer surfaces of the furnace shell or the equivalent temperature gradient.

5. The method of claim 4, wherein the method further comprises: determining a temperature of the non-ferrous metal in the molten bath; and adjusting the temperature of the non-ferrous metal in the molten bath to a target temperature. For regions with complex stress states, equivalent von Mises stress is used: It is the normal stress generated by the constraint of a non-uniform temperature field; It is shear stress; or With the allowable stress of the material The ratio is defined as a safety margin or safety indicator: in, This refers to the allowable stress value of the furnace shell material after considering the effects of fatigue and creep; after obtaining the temperature field information, thermal stress calculation and safety assessment are performed, including: calculating the equivalent thermal stress in each zone. ; Calculate the thermal stress safety index for each zone and with a pre-set security threshold Corresponding to the allowable stress Compare; if one or more partitions are found to be... The exposed area is in a state of excessive thermal stress or high risk; if all areas If all values ​​are within the safety threshold, the current control strategy will be maintained.

6. The method of claim 1, wherein the non-ferrous smelter vessel thermal stress mitigation method is characterized by: The whole furnace body is regarded as a thermal-structural dynamic system composed of multiple sub-zones coupled with each other; the temperature, heat flow and equivalent stress state variables of all sub-zones are combined to form a state vector through linearization of the relationship among heat flow, temperature and stress The cooling water flow, insulation opening degree, blowing intensity and air flow distribution execution variables are combined to form a control vector The material quantity, grade and fuel quantity are combined to form a disturbance vector A linearized or piecewise linearized state space model is established Wherein, the state vector includes the temperature, heat flow density and equivalent thermal stress state variables of the furnace shell of each sub-zone; the control input vector includes the cooling water flow, adjustable insulation plate opening degree, blowing intensity and distribution execution variables of each sub-zone; the disturbance vector represents external disturbance factors; the output vector is a measurable quantity, including the temperature and stress safety index of each sub-zone The overall goal of the control is to control the vector composed of the stress safety indexes of each sub-zone within the physically allowable range, while taking into account the maintenance of the reaction intensity and thermal efficiency in the furnace; A represents the state transition matrix; B represents the control input matrix; E represents the disturbance input matrix; C represents the output matrix; y(k) represents the output vector representing the set of physical quantities that can be actually obtained directly or indirectly through sensors at time k.

7. The method of claim 6, wherein the step of controlling thermal stress is performed by controlling the temperature of the non-ferrous metal bath. Based on the state space model, an optimization control strategy such as model predictive control is designed, considering a prediction horizon of , defining a desired stress index vector and a control amount reference value ; selecting a positive definite weight matrix and , constructing a multi-objective performance index function : wherein , is a weight matrix; by online optimization minimizing , an optimal control increment at the current time is obtained, and predictive reduction of the multi-zone thermal stress of the furnace body is realized. Performance indicators The mathematical basis for implementing the model predictive control strategy is a weighted quadratic form of the accumulated stress deviation and control deviation over the prediction horizon The optimal control input sequence is solved by minimizing to reduce the thermal stress level in each region while satisfying the constraints.

8. The method of claim 7, wherein the method further comprises: Stress safety indicators for each zone Long-term statistical analysis was conducted; a cumulative damage factor for each region was defined and calculated using a criterion similar to Miner's linear cumulative damage criterion. : in, For the first The duration of each heat load cycle To be at stress amplitude The lifespan at which material fatigue failure occurs; the cumulative damage factor reflects the fatigue wear of the furnace shell structure under various thermal stress cycles; when a certain area... Approaching or exceeding the warning threshold When this occurs, it indicates that the area is nearing the end of its fatigue life, and a maintenance alarm and recommendation will be issued.

9. The method of claim 1, wherein the method further comprises: determining a thermal stress of the non-ferrous metal smelting furnace body; and adjusting the thermal stress of the non-ferrous metal smelting furnace body. The non-ferrous metal bath smelting furnace body thermal stress regulation device comprises a furnace shell, a furnace lining, a cooling member, a flexible connecting member, a thermal buffer layer, an adjustable heat preservation structure, a sensor, a control unit, a cooling wall, a sliding connection assembly, a corrugated gasket, a first region, a second region, a third region and a fourth region.

10. A non-ferrous metal bath smelting furnace body thermal stress regulating device applied to the non-ferrous metal bath smelting furnace body thermal stress regulating method as claimed in any one of claims 1 to 9, characterized in that, The furnace shell is divided into a feeding end region, a middle high thermal load region, a copper or lead or nickel outlet end region and the like along the furnace length direction; the regions are divided according to the axis of the top blowing lance or the position of the side blowing port along the furnace width direction; the inlet and outlet temperatures and flow rates of the cooling water of each region are monitored, and the average heat flux density of the corresponding sub-region is calculated according to the monitoring data. The sliding connection assembly is arranged on the furnace shell and connected with the cooling wall; the cooling wall and the furnace lining are provided with the corrugated gasket on the inner side. The furnace shell, the furnace lining and the cooling member are divided into a plurality of thermal-mechanical coupling control regions according to the furnace body; the first region, the second region, the third region and the fourth region are divided. ​

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