Space temperature uniformity optimization method of industrial heating equipment and drying oven

Abstract

The invention relates to the technical field of industrial heat treatment, in particular to a space temperature uniformity optimization method of industrial heating equipment and a drying oven, and the method comprises the following steps: determining a reference symmetry axis in a box body of the equipment, symmetrically arranging a thermodynamic assembly around the reference symmetry axis, and constructing a closed circulating airflow path covering the thermodynamic assembly and a material chamber; the method comprises the following steps: acquiring a geometric structure, thermodynamic parameters and initial operation data of equipment to form a basic database, constructing a flow thermal coupling multi-physics field numerical model according to the basic database, and implanting thermophysical parameters and boundary conditions to generate a temperature field simulation model; heating control and airflow driving parameters are used as controlled variables to establish an association mapping model and perform cooperative regulation and control, temperature nodes are arranged in a cavity, time sequence data are collected to calculate a uniformity index, and if the index reaches the standard, optimized controlled parameters are output. According to the scheme, the temperature uniformity is improved by using a limited thermal dynamic part, the problems of reduction of an effective area of a distributed heat source and high energy consumption of multiple fans are avoided, and collaborative optimization of uniformity and economy is realized.

Description

Technical Field

[0001] This invention relates to the field of industrial heat treatment technology, and in particular to a method for optimizing the spatial temperature uniformity of industrial heating equipment and an oven. Background Technology

[0002] As a widely used heat treatment equipment in the industrial production field, the core function of the oven is to carry out key heat treatment processes such as drying, curing and baking on various materials by creating a controllable thermal environment, providing important technical support for the production and processing of industrial products.

[0003] However, in current technological practices, existing ovens generally face technical bottlenecks, primarily stemming from core factors such as unreasonable internal airflow organization design, lack of optimized heating element layout, and suboptimal duct structure arrangement. As a result, the temperature field uniformity within the oven is poor, with significant temperature deviations between different areas. This technical deficiency directly leads to localized overheating or underheating of materials during heat treatment, resulting in inconsistent product quality within the same batch and decreased performance stability between different batches. It also significantly increases the rework rate, adversely affecting industrial production efficiency and cost control.

[0004] To improve the aforementioned problem of poor temperature field uniformity, the industry has proposed and tried two types of solutions: one is to use multiple distributed heat sources. Although this solution can compensate for the temperature difference between different areas to a certain extent, it will create multiple local high-temperature zones in the oven, which will squeeze the space for a uniform temperature field that meets the process requirements. Ultimately, this will significantly reduce the volume of the effective heating zone in the oven, making it difficult to meet the production needs of large-scale or high-consistency requirements. The second solution is to use multiple fans working in tandem. This solution promotes temperature uniformity by enhancing airflow disturbance, but the simultaneous operation of multiple fans means a sharp increase in equipment energy consumption. This not only directly increases the daily operating cost of the equipment, but the complex control logic required for multiple fans to work together also further reduces the energy utilization efficiency of the entire heating system, which is contrary to the current trend of energy conservation and consumption reduction advocated in the industrial field.

[0005] Therefore, under the premise that the number of heating devices and fans are strictly limited (i.e. without relying on increasing the number of core components), how to effectively improve the distribution characteristics of the flow field and heat field inside the oven by rationally arranging heating elements, optimizing the airflow organization and duct structure design, and finally achieving high temperature uniformity inside the oven, has become a key problem that urgently needs to be solved in the current oven technology field. Summary of the Invention

[0006] Therefore, the technical problem to be solved by the present invention is to overcome the defect of poor uniformity of temperature field in the internal space of existing ovens. Furthermore, the multiple distributed heat source schemes used to improve this defect will squeeze the uniform temperature field space, resulting in a significant reduction in the volume of the effective heating zone. The multiple fan coordination schemes will drastically increase the energy consumption of the equipment and reduce the energy utilization efficiency of the system. Thus, the present invention provides a method for optimizing the spatial temperature uniformity of industrial heating equipment and an oven.

[0007] The method for optimizing the spatial temperature uniformity of the industrial heating equipment includes the following steps: S1: Determine a reference axis of symmetry within the equipment housing. Based on the reference axis of symmetry, rotate symmetrically arrange a thermal component including a heating module and an airflow drive module to form a closed-loop airflow path within the housing that covers the thermal component and the chamber where the material to be processed is located. S2: Acquire geometric structure data, thermal component parameter data and initial operation data of industrial heating equipment to form a basic database of equipment, which includes: three-dimensional geometric coordinate data of the working chamber of industrial heating equipment, power parameters and installation position coordinate data of heating module, rotation speed parameters and shaft position data of airflow drive module, thermal property parameters of each component of equipment and ambient temperature data and initial temperature distribution data of chamber during initial operation of equipment. S3: Based on the aforementioned equipment database, construct a multiphysics numerical model that includes fluid flow and heat transfer coupling, and generate a temperature field simulation data model for industrial heating equipment by embedding thermal property parameters and boundary conditions. S4: Extract the heating control parameters and airflow driving parameters from the temperature field simulation data model as controlled variables, establish a correlation mapping model between the controlled variables and the temperature field data of the equipment chamber, and perform collaborative variable regulation based on the model; S5: Within the chamber space of the temperature field simulation data model, temperature acquisition data nodes are set up to collect temperature time-series data from each node. Based on the temperature time-series data, spatial temperature uniformity evaluation index data is obtained. S6: Compare the spatial temperature uniformity evaluation index data with the preset temperature uniformity threshold: If the spatial temperature uniformity evaluation index data does not meet the threshold requirements, return to step S4 and iteratively correct the control parameters of the controlled variable; If the spatial temperature uniformity evaluation index data meets the threshold requirements, the optimized controlled variable parameters are output.

[0008] In one embodiment of the present invention, the method for generating the temperature field simulation data model of the industrial heating equipment in step S3 is as follows: S31: Based on the thermal component parameter data, structural parameters and initial operating data in the equipment basic database, construct a multiphysics numerical model that couples the fluid flow process and the heat transfer process; S32: Based on the geometric structure data in the equipment basic database, establish a three-dimensional geometric data model with a preset scale. According to the numerical solution adaptation requirements of the multiphysics numerical model, simplify the non-target flow field region and non-heat transfer target structure in the three-dimensional geometric data model, retain the target geometric features related to flow field evolution and heat exchange, and obtain the simplified three-dimensional geometric data model. S33: The simplified three-dimensional geometric data model is meshed using a numerical discretization algorithm to generate a discrete mesh dataset containing mesh node coordinate data and mesh cell topological relationship data. S34: Based on the input parameter adaptation requirements of the multiphysics numerical model, the thermal property parameters in the thermal component parameter data are mapped to the corresponding grid cells in the discrete grid dataset. At the same time, pressure rise-flow characteristic data is configured for the airflow drive module, and constant power heat source data is configured for the heating module to form a temperature field simulation data model.

[0009] In one embodiment of the present invention, the multiphysics numerical model includes a fluid flow control model and a heat transfer control model. The fluid flow control model characterizes the fluid flow process, and the heat transfer control model characterizes the heat transfer process.

[0010] In one embodiment of the present invention, the fluid flow control model adopts a compressible Reynolds-averaged Navier-Stokes k-ε turbulence control model, whose control equations include: The mass conservation equation is as follows: ,in This represents the average fluid density. For time, A density-weighted average of velocities. It is a divergence operator; The momentum conservation equation is as follows: ,in, For average pressure, For fluid dynamic viscosity, For turbulent viscosity, For turbulent kinetic energy, For unit tensors, The vector of gravitational acceleration. It serves as an equivalent momentum source for fans or throttling components. Represents the tensor cross product; The turbulent kinetic energy The transport equations are as follows: ,in It is the turbulent diffusion constant. , For shear heat generation, For buoyancy-induced heat generation, This is a compressible expansion correction term. The turbulent energy dissipation rate; The turbulent energy dissipation rate The transport equations are as follows: ,in It is the turbulent diffusion constant. These are model constants.

[0011] In one embodiment of the present invention, the heat transfer control model adopts a conjugate heat transfer control model, and its control equations include: The energy equation for the fluid domain is as follows: ,in For isobaric specific heat, For fluid temperature, For effective thermal conductivity, As a heat source or equivalent heat source, This represents the average fluid density. A density-weighted average of velocities; The energy equation for the solid domain is as follows: ,in For solid density, It is the specific heat at constant pressure of a solid. For solid temperature, Thermal conductivity of solids As a solid volume heat source, It is a divergence operator.

[0012] In one embodiment of the present invention, the numerical discretization algorithm for meshing the simplified three-dimensional geometric data model is any one of the following: finite element method, finite volume method, finite difference method, spectral method, and spectral element method.

[0013] In one embodiment of the present invention, in step S5, the method for obtaining the spatial temperature uniformity evaluation index data is as follows: Nine temperature data acquisition nodes, arranged in a three-dimensional distribution, are selected within the chamber space of the temperature field simulation data model. Temperature time-series data from each node are simultaneously acquired during the heating process, denoted as […]. ; Based on the temperature time series data, calculate the instantaneous average temperature value. : ; Based on the instantaneous average temperature value Calculate spatial temperature uniformity evaluation index data : , This represents the maximum instantaneous temperature. This represents the minimum instantaneous temperature.

[0014] The present invention also provides an oven, comprising: a control module, a housing, a functional cavity disposed within the housing, a thermal component, and an airflow guiding component; The functional cavity includes a working chamber for containing the material to be processed, and a heating chamber for installing the thermal assembly; A reference axis of symmetry is defined within the housing, and the thermal motion component and the airflow guiding component are arranged symmetrically around the reference axis of symmetry, so that a closed circulating airflow path covering the working chamber and the thermal motion component is formed within the housing; The control module executes the method described above to improve the temperature uniformity of the oven space, obtains optimized control parameters, and uses these control parameters to coordinate the control of the thermal components, thereby improving the temperature uniformity of the working chamber space.

[0015] In one embodiment of the present invention, the thermal assembly includes a heating module for providing a heat source and an airflow drive module for driving airflow circulation; the power output axis of the airflow drive module coincides with the reference symmetry axis; the heating module is distributed in a concentric ring structure or an equally divided arc segment structure based on the reference symmetry axis.

[0016] In one embodiment of the present invention, the airflow guiding component connects the heating chamber and the working chamber, and includes a guide plate, a return air channel corresponding to the airflow driving module, and an air supply channel corresponding to the heating module; the return air channel is located in the central area of ​​the guide plate, and the air supply channel is arranged around the return air channel at equal angular intervals and equal channel dimensions.

[0017] Compared with the prior art, the above-described technical solution of the present invention has the following advantages: This invention, by determining a reference axis of symmetry and achieving a rotationally symmetrical layout of the thermal components and airflow guiding structure around it, combined with a closed-loop airflow path design covering the working chamber and the thermal components, effectively optimizes the airflow organization and thermal field distribution within the chamber under the condition of a limited number of heating devices and fans, significantly improving the temperature uniformity of the working chamber. It avoids the problem of reduced effective heating area caused by multiple distributed heat sources or multiple fans in parallel, as well as the high energy consumption and low energy efficiency defects caused by the former. Simultaneously, by establishing a compressible turbulent-conjugate heat transfer coupled temperature field simulation model and implementing coordinated control of the thermal components, it can ensure that the chamber temperature rapidly approaches and stably maintains the target value, and accurately evaluate temperature uniformity through simulation verification, achieving synergistic optimization of temperature control accuracy, energy economy, and temperature uniformity. Attached Figure Description

[0018] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0019] Figure 1 This is a schematic flowchart of a method for optimizing the spatial temperature uniformity of an industrial heating device provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of an oven structure provided in an embodiment of the present invention; Figure 3 yes Figure 2 A partial structural diagram of the oven shown; Figure 4 This is a schematic diagram of the airflow guiding component provided in an embodiment of the present invention.

[0020] Explanation of reference numerals in the accompanying drawings: 1. Housing; 11. Air outlet duct; 12. Balance valve; 2. Functional chamber; 21. Working chamber; 22. Heating chamber; 3. Thermal component; 31. Heating module; 32. Airflow drive module; 321. Fan; 322. Servo motor; 4. Airflow guiding component; 41. Deflector plate; 42. Return air duct; 43. Supply air duct; 5. Door. Detailed Implementation

[0021] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention. Example

[0022] Reference Figure 1 As shown, the present invention provides a method for optimizing the spatial temperature uniformity of industrial heating equipment, specifically including the following steps: S1: Determine a reference axis of symmetry within the equipment housing. Based on the reference axis of symmetry, rotate symmetrically arrange a thermal component including a heating module and an airflow drive module to form a closed-loop airflow path within the housing that covers the thermal component and the chamber where the material to be processed is located. S2: Acquire geometric structure data, thermal component parameter data and initial operation data of industrial heating equipment to form a basic database of equipment, which includes: three-dimensional geometric coordinate data of the working chamber of industrial heating equipment, power parameters and installation position coordinate data of heating module, rotation speed parameters and shaft position data of airflow drive module, thermal property parameters of each component of equipment and ambient temperature data and initial temperature distribution data of chamber during initial operation of equipment. S3: Based on the aforementioned equipment database, construct a multiphysics numerical model that includes fluid flow and heat transfer coupling, and generate a temperature field simulation data model for industrial heating equipment by embedding thermal property parameters and boundary conditions. S4: Extract the heating control parameters and airflow driving parameters from the temperature field simulation data model as controlled variables, establish a correlation mapping model between the controlled variables and the temperature field data of the equipment chamber, and perform collaborative variable regulation based on the model; S5: Within the chamber space of the temperature field simulation data model, temperature acquisition data nodes are set up to collect temperature time-series data from each node. Based on the temperature time-series data, spatial temperature uniformity evaluation index data is obtained. S6: Compare the spatial temperature uniformity evaluation index data with the preset temperature uniformity threshold: If the spatial temperature uniformity evaluation index data does not meet the threshold requirements, return to step S4 and iteratively correct the control parameters of the controlled variable; If the spatial temperature uniformity evaluation index data meets the threshold requirements, the optimized controlled variable parameters are output.

[0023] Further, in step S1, the method for determining a reference axis of symmetry within the equipment housing is as follows: taking the effective flow domain of the chamber where the material to be processed is located as the priority criterion, and combining the geometric model and functional opening constraints of the industrial heating equipment, candidate axes that are consistent with the natural symmetry of the effective flow domain are identified, and the axis passing through the geometric center of the effective flow domain is preferred; if there are two or more equivalent candidate axes, the axis that is consistent with or can cooperate with the main direction of natural convection is preferred as the reference axis of symmetry.

[0024] Furthermore, in this embodiment, the method for generating the temperature field simulation data model of the industrial heating equipment in S3 is as follows: S31: Based on the thermal component parameter data, structural parameters and initial operating data in the equipment basic database, construct a multi-physics numerical model that couples the fluid flow process and the heat transfer process. It includes a fluid flow control model and a heat transfer control model. The fluid flow control model characterizes the fluid flow process, and the heat transfer control model characterizes the heat transfer process. S32: Based on the geometric structure data in the equipment basic database, establish a three-dimensional geometric data model with a preset scale (1:1). According to the numerical solution adaptation requirements of the multiphysics numerical model, simplify the non-target flow field regions (such as irrelevant protrusions and grooves) and non-heat transfer target structures (such as non-heat-conducting parts of fixed supports) in the three-dimensional geometric data model, retain the target geometric features related to flow field evolution and heat exchange (such as channel shape and heating module outline), reduce the computational complexity, and obtain the simplified three-dimensional geometric data model. S33: The simplified three-dimensional geometric data model is meshed using a numerical discretization algorithm to generate a discrete mesh dataset containing mesh node coordinate data and mesh cell topological relationship data; Optionally, the numerical discretization algorithm for meshing the simplified three-dimensional geometric data model can be any one of the following: finite element method, finite volume method, finite difference method, spectral method, and spectral element method. S34: Based on the input parameter adaptation requirements of the multiphysics numerical model, the thermal property parameters in the thermal component parameter data are mapped to the corresponding grid cells in the discrete grid dataset. At the same time, pressure rise-flow characteristic data is configured for the airflow drive module, and constant power heat source data is configured for the heating module to form a temperature field simulation data model.

[0025] Specifically, in S31, the fluid flow control model adopts a compressible Reynolds-averaged Navier-Stokes k-ε turbulence control model, whose governing equations include: The mass conservation equation is as follows: ,in This represents the average fluid density. For time, A density-weighted average of velocities. It is a divergence operator; The momentum conservation equation is as follows: ,in, For average pressure, For fluid dynamic viscosity, For turbulent viscosity, For turbulent kinetic energy, For unit tensors, The vector of gravitational acceleration. It serves as an equivalent momentum source for fans or throttling components. Represents the tensor cross product; The turbulent kinetic energy The transport equations are as follows: ,in It is the turbulent diffusion constant. , For shear heat generation, For buoyancy-induced heat generation, This is a compressible expansion correction term. The turbulent energy dissipation rate;

[0026] The turbulent energy dissipation rate The transport equations are as follows: ,in It is the turbulent diffusion constant. These are model constants.

[0027] Specifically, the heat transfer control model adopts a conjugate heat transfer control model, and its control equations include:

[0028] The energy equation for the fluid domain is as follows: ,in For isobaric specific heat, For fluid temperature, For effective thermal conductivity, A heat source or equivalent heat source;

[0029] The energy equation for the solid domain is as follows: ,in For solid density, It is the specific heat at constant pressure of a solid. For solid temperature, Thermal conductivity of solids As a solid volume heat source, It is a divergence operator.

[0030] In step S4, heating control parameters (such as heating power) are extracted from the temperature field simulation data model. ) and gas drive parameters (fan speed) Using the temperature field simulation data model as the controlled variable, a correlation mapping relationship between the controlled variable and the chamber temperature field data is established to clarify the influence of heating power and fan speed on temperature distribution. Any one of PID control, feedforward-feedback coordinated control, model predictive control (MPC), or fuzzy control is employed to rapidly approach and stably maintain the target temperature at the average chamber temperature. With the goal of suppressing temperature differences in the space, the heating module and the fan are controlled in a coordinated manner to avoid temperature fluctuations or a decrease in uniformity caused by adjusting a single parameter.

[0031] In step S5, a nine-point temperature measurement method is used to quantitatively evaluate the temperature uniformity: nine temperature data acquisition nodes distributed in a three-dimensional manner are selected in the chamber where the material to be processed is located. Temperature time-series data of each node are collected synchronously during the heating process and recorded as follows: ; Based on the temperature time series data, calculate the instantaneous average temperature value. : ; Based on the instantaneous average temperature value Maximum instantaneous temperature and instantaneous minimum temperature Calculate spatial temperature uniformity evaluation index data : If a single value evaluation is required, it can be performed within the selected heating time window. The maximum value or the average value over time is taken as the comprehensive criterion.

[0032] The calculated Compare with the preset temperature uniformity threshold: If If the threshold requirement is not met, return to step S4, correct the control parameters of heating power and fan speed based on the temperature field simulation results, and re-execute the coordinated control and uniformity evaluation until the requirement is met; if The optimized heating power is output after meeting the threshold requirements. and fan speed , which serves as the control parameter for the actual operation of the oven.

[0033] Example 2:

[0034] like Figures 2-4 As shown, the present invention also provides an oven, including: a control module, a housing 1, a functional cavity 2 disposed within the housing 1, a thermal assembly 3, an airflow guiding assembly 4, and a door 5; The functional cavity 2 includes a working chamber 21 for containing the material to be processed, and a heating chamber 22 for installing the thermal assembly 3. A reference axis of symmetry is defined within the housing 1. The thermal motion component 2 and the airflow guiding component 4 are arranged symmetrically around the reference axis of symmetry, so that a closed circulating airflow path covering the working chamber 21 and the thermal motion component 3 is formed within the housing 1. The geometry, path length, and equivalent resistance of the circulating airflow path are consistent in all circumferential directions. The control module executes the method described in Embodiment 1 to improve the spatial temperature uniformity of the oven, obtains optimized control parameters, and uses the control parameters to perform coordinated control on the thermal component 3, thereby improving the spatial temperature uniformity of the working chamber 21.

[0035] A reference axis of symmetry is determined within the chamber 1. The method for selecting the reference axis of symmetry is as described in Embodiment 1, including: using the effective flow domain of the working chamber 21 as the priority criterion, and combining the geometric model of the oven and the functional opening constraints, identifying candidate axes that are consistent with the natural symmetry of the effective flow domain, and preferentially selecting the axis that passes through the geometric center of the effective flow domain; if there are two or more equivalent candidate axes, then the axis that is consistent with or can cooperate with the main direction of natural convection is preferentially selected as the reference axis of symmetry.

[0036] In this embodiment, the housing 1 has an approximately cubic structure. The candidate axis is the line connecting the center points of any pair of opposite faces. Combining the natural convection characteristics of the gas forming from bottom to top along the direction of gravity, the line connecting the center points of the top and bottom surfaces of the housing 1 is finally selected as the reference axis of symmetry. This axis provides a unified constraint reference for the subsequent layout of thermal components and the design of the air duct structure, ensuring that the airflow path around the axis has isotropic geometric characteristics and engineering feasibility.

[0037] Furthermore, an insulation layer made of polyurethane foam is provided between the outer shell and the inner shell of the housing 1 to isolate the circulating airflow channel from the outside, ensuring that the airflow path is not directly connected to the outside under normal operating conditions. In addition, the housing 1 is equipped with an air outlet duct 11 and a balance valve 12 connected to the working chamber 21. The balance valve 12 is connected to the air outlet duct 11, and the central axes of both are collinear with the reference axis of symmetry. Its core functions are safety protection and micro-pressure regulation; it remains closed or flow-limited under non-differential pressure conditions, does not participate in the internal closed-loop airflow, and avoids disrupting the circumferential isomorphism of the airflow organization.

[0038] Furthermore, the thermal assembly 3 includes a heating module 31 for providing a heat source and an airflow drive module 32 for driving airflow circulation. The heating module 31 employs an annular heating wire assembly, distributed in a concentric ring structure with a reference axis of symmetry as the center, forming heating rings of equal diameter and spacing to ensure circumferential heating uniformity; the power parameters of the heating module 31 can be adjusted by a control module to provide a stable heat source for the airflow.

[0039] The airflow drive module 32 consists of a fan 321 and a servo motor 322. The rotating shaft of the fan 321 coincides with the reference axis of symmetry. The servo motor 322 is used to adjust the rotation speed of the fan 321 to provide power for airflow circulation. Its pressure rise-flow characteristic data is pre-configured into the temperature field simulation data model to adapt to different working conditions.

[0040] Furthermore, the airflow guiding component 4 is disposed between the working chamber 21 and the heating chamber 22 to construct a uniform airflow channel, which includes a guide plate 41, a return air channel 42 corresponding to the airflow driving module 32, and an air supply channel 43 corresponding to the heating module 31.

[0041] The guide plate 41 divides the functional cavity 2 into a working chamber 21 and a heating chamber 22. The return air channel 42 is set as a circular hole in the central area of ​​the guide plate 41, corresponding to the position of the fan 321, and is used to concentrate the return air from the working chamber 21 into the heating chamber. Its hole diameter matches the size of the air outlet of the fan 321.

[0042] The air supply channel 43 is configured as an annular array of slots on the guide plate 41 along the circumference of the return air channel 42 with equal angular spacing and equal channel size, corresponding to the annular distribution of the heating module 31 (annular heating wire group), to ensure that the heated airflow is uniformly delivered into the working chamber; the radial position, opening width, and arc length of each slot are consistent with the effective ventilation cross section to ensure balanced circumferential airflow resistance.

[0043] When the hatch 5 is closed, the fan 321 draws the return air from the working chamber 21 into the heating chamber 22 from the return air channel 42 corresponding to its position on the guide plate 41. The gas entering the heating chamber 22 flows through the annular heating wire group, obtains heat and is pressurized, and then is evenly sent into the working chamber 21 through the air supply channel 43 corresponding to the position of the heating device on the guide plate 41.

[0044] After the gas completes the convective heat exchange of the material in the working chamber 21, it flows back into the heating chamber 22 through the return air channel 42, thus forming an internal circulation path of "inhalation-heating-intake-return". This circulation path simultaneously encloses the heating module 31 and the working chamber 21, realizing continuous heat delivery and recycling.

[0045] The control module includes nine temperature sensors arranged in a three-dimensional pattern within the working chamber 21 to synchronously collect time-series temperature data at each point. Furthermore, the control module is connected to the thermal actuator 3 and sequentially executes the steps of receiving temperature data, running a temperature field simulation model, implementing a collaborative control strategy, and iteratively correcting control parameters, ultimately outputting the optimized heating power. With fan speed parameters .

[0046] This embodiment employs a symmetrical structural design to ensure that the closed-loop airflow path has a consistent geometric shape and resistance characteristics in all circumferential directions, avoiding local airflow stagnation or uneven velocity. Combined with a fluid-thermal coupling simulation model and a collaborative control strategy, heating and airflow parameters are precisely controlled, effectively suppressing spatial temperature differences. Simulation verification shows that the oven using this method exhibits a relatively low relative error in the spatial temperature uniformity of the working chamber 21. It can be stably controlled within a preset threshold without increasing the number of heating devices and fans. Compared with existing technologies, it avoids the problem of reduced effective heating area caused by distributed heat sources, ensuring the needs of large-scale production. It overcomes the high energy consumption and low energy efficiency defects of multi-fan systems, reducing operating costs. It achieves synergistic optimization of temperature control accuracy, uniformity effect and economy, and is suitable for industrial heat treatment scenarios with high requirements for temperature consistency.

[0047] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0048] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0049] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0050] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0051] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for optimizing the spatial temperature uniformity of an industrial heating device, characterized in that, include: S1: Determine a reference axis of symmetry within the equipment housing. Based on the reference axis of symmetry, rotate symmetrically arrange a thermal component including a heating module and an airflow drive module to form a closed-loop airflow path within the housing that covers the thermal component and the chamber where the material to be processed is located. S2: Acquire geometric structure data, thermal component parameter data and initial operation data of industrial heating equipment to form a basic database of equipment, which includes: three-dimensional geometric coordinate data of the working chamber of industrial heating equipment, power parameters and installation position coordinate data of heating module, rotation speed parameters and shaft position data of airflow drive module, thermal property parameters of each component of equipment and ambient temperature data and initial temperature distribution data of chamber during initial operation of equipment. S3: Based on the aforementioned equipment database, construct a multiphysics numerical model that includes fluid flow and heat transfer coupling, and generate a temperature field simulation data model for industrial heating equipment by embedding thermal property parameters and boundary conditions. S4: Extract the heating control parameters and airflow driving parameters from the temperature field simulation data model as controlled variables, establish a correlation mapping model between the controlled variables and the temperature field data of the equipment chamber, and perform collaborative variable regulation based on the model; S5: Within the chamber space of the temperature field simulation data model, temperature acquisition data nodes are set up to collect temperature time-series data from each node. Based on the temperature time-series data, spatial temperature uniformity evaluation index data is obtained. S6: Compare the spatial temperature uniformity evaluation index data with the preset temperature uniformity threshold: If the spatial temperature uniformity evaluation index data does not meet the threshold requirements, return to step S4 and iteratively correct the control parameters of the controlled variable; If the spatial temperature uniformity evaluation index data meets the threshold requirements, the optimized controlled variable parameters are output.

2. The method for optimizing the spatial temperature uniformity of industrial heating equipment according to claim 1, characterized in that, In S3, the method for generating temperature field simulation data models of industrial heating equipment is as follows: S31: Based on the thermal component parameter data, structural parameters and initial operating data in the equipment basic database, construct a multiphysics numerical model that couples the fluid flow process and the heat transfer process; S32: Based on the geometric structure data in the equipment basic database, establish a three-dimensional geometric data model with a preset scale. According to the numerical solution adaptation requirements of the multiphysics numerical model, simplify the non-target flow field region and non-heat transfer target structure in the three-dimensional geometric data model, retain the target geometric features related to flow field evolution and heat exchange, and obtain the simplified three-dimensional geometric data model. S33: The simplified three-dimensional geometric data model is meshed using a numerical discretization algorithm to generate a discrete mesh dataset containing mesh node coordinate data and mesh cell topological relationship data. S34: Based on the input parameter adaptation requirements of the multiphysics numerical model, the thermal property parameters in the thermal component parameter data are mapped to the corresponding grid cells in the discrete grid dataset. At the same time, pressure rise-flow characteristic data is configured for the airflow drive module, and constant power heat source data is configured for the heating module to form a temperature field simulation data model.

3. The method for optimizing the spatial temperature uniformity of industrial heating equipment according to claim 2, characterized in that, The multiphysics numerical model includes a fluid flow control model and a heat transfer control model. The fluid flow control model characterizes the fluid flow process, and the heat transfer control model characterizes the heat transfer process.

4. The method for optimizing the spatial temperature uniformity of industrial heating equipment according to claim 3, characterized in that, The fluid flow control model adopts the compressible Reynolds-averaged Navier-Stokes k-ε turbulence control model, and its governing equations include: The mass conservation equation is as follows: ,in This represents the average fluid density. For time, A density-weighted average of velocities. For divergence operators; The momentum conservation equation is as follows: ,in, For average pressure, For fluid dynamic viscosity, For turbulent viscosity, For turbulent kinetic energy, For unit tensors, The vector of gravitational acceleration. It serves as an equivalent momentum source for fans or throttling components. Represents the tensor cross product; The turbulent kinetic energy The transport equation is as follows: ,in It is the turbulent diffusion constant. , For shear heat generation, For buoyancy-induced heat generation, This is a compressible expansion correction term. The turbulent energy dissipation rate; The turbulent energy dissipation rate The transport equation is as follows: ,in It is the turbulent diffusion constant. These are model constants.

5. The method for optimizing the spatial temperature uniformity of industrial heating equipment according to claim 3, characterized in that, The heat transfer control model adopts a conjugate heat transfer control model, and its control equations include: The energy equation for the fluid domain is as follows: ,in For isobaric specific heat, For fluid temperature, For effective thermal conductivity, As a heat source or equivalent heat source, This represents the average fluid density. Density-weighted average of velocities; The energy equation for the solid domain is as follows: ,in For solid density, It is the specific heat at constant pressure of a solid. For solid temperature, Thermal conductivity of solids As a solid volume heat source, It is a divergence operator.

6. The method for optimizing the spatial temperature uniformity of industrial heating equipment according to claim 2, characterized in that, The numerical discretization algorithm for meshing the simplified three-dimensional geometric data model can be any one of the following: finite element method, finite volume method, finite difference method, spectral method, and spectral element method.

7. The method for optimizing the spatial temperature uniformity of industrial heating equipment according to claim 1, characterized in that, In S5, the method for obtaining the spatial temperature uniformity evaluation index data is as follows: Nine temperature data acquisition nodes, arranged in a three-dimensional distribution, are selected within the chamber space of the temperature field simulation data model. Temperature time-series data from each node are simultaneously acquired during the heating process, denoted as […]. ; Based on the temperature time series data, calculate the instantaneous average temperature value. : ; Based on the instantaneous average temperature value Calculate spatial temperature uniformity evaluation index data : , This represents the maximum instantaneous temperature. This represents the minimum instantaneous temperature.

8. An oven, characterized in that, include: Control module, housing, functional cavities disposed within the housing, thermodynamic components, and airflow guiding components; The functional cavity includes a working chamber for containing the material to be processed, and a heating chamber for installing the thermal assembly; A reference axis of symmetry is defined within the housing, and the thermal motion component and the airflow guiding component are arranged symmetrically around the reference axis of symmetry, so that a closed circulating airflow path covering the working chamber and the thermal motion component is formed within the housing; The control module executes the method described in any one of claims 1 to 7 to improve the spatial temperature uniformity of the oven, obtains optimized control parameters, and uses the control parameters to perform coordinated control of the thermal components, thereby improving the spatial temperature uniformity of the working chamber.

9. The drying oven according to claim 8, characterized in that, The thermal assembly includes a heating module for providing a heat source and an airflow drive module for driving airflow circulation; the power output axis of the airflow drive module coincides with the reference symmetry axis; the heating module is distributed in a concentric ring structure or an equally divided arc segment structure based on the reference symmetry axis.

10. The drying oven according to claim 9, characterized in that, The airflow guiding component connects the heating chamber and the working chamber, and includes a guide plate, a return air channel corresponding to the airflow driving module, and an air supply channel corresponding to the heating module; the return air channel is located in the central area of ​​the guide plate, and the air supply channel is arranged around the return air channel with equal angular spacing and equal channel dimensions.

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