Foamed ceramic insulation board automatic feeding and discharging energy-saving production system

Abstract

The present application relates to the technical field of energy-saving management and control, and discloses an automatic feeding and discharging energy-saving production system for foamed ceramic insulation boards. The present application aims to solve the technical pain point of abnormally high energy consumption caused by blind parameter setting and heat recovery fragmentation in the existing high-temperature calcination process. The present application realizes the overall production planning and the maximum utilization of waste heat by constructing a deduction mechanism based on physical feature constraints and a multi-temperature zone dynamic closed-loop architecture. The core lies in extracting the real densification parameters of pre-sintering, taking the airflow and thermal hysteresis effect as spatial constraints to deduce the optimal calcination parameters; relying on a double-layer heat exchange chamber to establish a two-way temperature constraint, combining with the cold-state heat equivalent decreasing compensation to realize efficient preheating and safe cooling. Through self-adaptive calibration closed loop, the energy efficiency ratio of finished products is significantly improved, and the ability to respond to complex industrial environment fluctuations is enhanced.

Description

Technical Field

[0001] This invention relates to the field of energy-saving control technology, and more specifically, to an automatic loading and unloading energy-saving production system for foamed ceramic insulation boards. Background Technology

[0002] Foamed ceramic insulation boards, as a new type of inorganic flame-retardant insulation material, are widely used in building exterior wall insulation, industrial kiln insulation, cold chain logistics, and special environmental protection due to their excellent fire resistance, heat insulation, aging resistance, and lifespan comparable to that of buildings. With the continuous improvement of modern building energy efficiency standards and industrial insulation requirements, the market demand and application scale of foamed ceramic insulation boards are showing a sustained expansion trend.

[0003] With the deepening of the concepts of green manufacturing and energy conservation and emission reduction, various industries have put forward higher requirements for the low-carbon and high-efficiency production of foamed ceramic insulation boards.

[0004] The parameter setting for high-temperature calcination processes mainly relies on manual experience or fixed preset curves. In actual production, in order to ensure that the products are fully calcined, the industry generally adopts a crude approach of extending the calcination time or blindly increasing the overall heating power. This not only leads to abnormally high energy consumption, but also often causes local deformation or insufficient strength of products in the same furnace due to uneven heating, resulting in unstable finished product yield.

[0005] The flow and recovery of heat energy within production systems are mostly fragmented or semi-fragmented. Existing waste heat recovery devices are often static physical transfer devices. Especially during production line start-up or when operating conditions fluctuate, they can only mechanically rely on external auxiliary heat sources for high-power compensation. This lack of dynamic and coordinated heat management also results in serious energy waste. Summary of the Invention

[0006] In view of the aforementioned existing problems, the present invention is proposed.

[0007] Therefore, this invention provides an automatic loading and unloading energy-saving production system for foamed ceramic insulation boards, which solves the technical pain point of excessively high energy consumption caused by blind parameter setting and fragmented heat recovery in existing high-temperature calcination processes.

[0008] To solve the above-mentioned technical problems, the present invention provides the following technical solution: This invention provides an automatic loading and unloading energy-saving production system for foamed ceramic insulation boards, which includes the following modules: Thermodynamic benchmark testing module: used to perform pre-sintering tests. The pre-sintering process is controlled by the gradient temperature control module. During the process, the data acquisition module continuously records the pre-sintering parameters, and the thermodynamic parameter calculation module calculates the thermodynamic parameters of the material by analyzing the pre-sintering parameters. Calcination parameter optimization module: The calcination simulation module performs multi-dimensional variable calcination simulation based on the thermodynamic parameters, and the calcination optimization module calculates the theoretical optimal calcination parameters, including the number of loaded pieces per batch and the processing time per batch, based on the calcination simulation results. Heat exchange fluid simulation module: The fluid simulation module performs flow field simulation and deduction on the double-layer convection heat exchange chamber based on the number of single-batch loading plates, the single-batch processing time, and bidirectional temperature constraints. The fluid optimization module selects low-energy-consumption air transmission implementation schemes based on the flow field simulation and deduction results. Cold state compensation calculation module: Based on the air transmission implementation scheme, calculate the heat gap of the first batch of green billets before the formation of the waste heat circulation closed loop in the double-layer convection heat exchange chamber, and generate the corresponding initial external heat compensation command.

[0009] As a preferred embodiment of the automatic loading and unloading energy-saving production system for foamed ceramic insulation boards described in this invention, the specific operations of the gradient temperature control module controlling the pre-sintering process include: The starting temperature reference for the pre-sintering environment is set based on the temperature at which a thermochemical reaction is determined to be non-existent. Starting from the initial temperature reference, a stepped heating action is performed alternately according to the preset temperature increase range and the fixed heat preservation time; During the execution of the stepped heating action, real-time monitoring data fed back by the data acquisition module is received synchronously; after a significant initial curve shift indicating an internal reaction of the material is detected in the feedback data, the current heating rate is maintained, the heat preservation step in the stepped heating action is skipped, until the shift process ends and the temperature returns to the normal physical heating baseline state, and the stepped heating action is resumed. The pre-sintering test is terminated after the last data shift state characterizing the densification shrinkage process is detected, by repeating the response curve shift to switch the heating mode.

[0010] As a preferred embodiment of the automatic loading and unloading energy-saving production system for foamed ceramic insulation boards described in this invention, the data acquisition module is configured to continuously acquire multi-dimensional sensor data throughout the entire pre-sintering test and actual production cycle of the system. Specific acquisition operations include: The optical volume change data of the green body during the heating process are collected by a laser profile sensor installed at the high-temperature observation window of the main kiln. The actual ambient temperature of the kiln and the actual temperature of the green body are collected by thermocouples arranged on the inner wall of the main kiln and infrared radiation thermometers that are non-contact and aligned with the surface of the green body. The actual preheating temperature of the upper preheating zone and the actual cooling temperature of the lower cooling zone are collected by a sensor network deployed in the double-layer convection heat exchange chamber.

[0011] As a preferred embodiment of the automatic loading and unloading energy-saving production system for foamed ceramic insulation boards described in this invention, the specific calculation process of the thermodynamic parameter calculation module includes: By combining the optical volume change data of the green blank with the actual temperature of the green blank, the starting point of the last data offset, which represents the continuous shrinkage of the volume, is identified after the green blank undergoes an initial expansion offset under heat and returns to a stable state. The actual temperature of the green blank corresponding to the starting point of the last data offset is extracted as the shrinkage initiation temperature of the material. Calculate the dynamic temperature difference between the actual ambient temperature of the kiln and the actual temperature of the green body, generate the original heat absorption curve reflecting the entire heating process, and smooth the original heat absorption curve to obtain a smooth heat absorption curve. The segment corresponding to the last data shift process in the smooth thermal absorption curve is extracted as the densification characteristic curve. The first derivative of the densification characteristic curve is calculated to find the extreme point of the theoretical optimal heat absorption temperature characterizing the material during the densification process, and the temperature corresponding to the extreme point is taken as the theoretical optimal heat absorption temperature. Perform second derivative calculation on the densification characteristic curve, and extract two adjacent inflection points where the second derivative value is equal to zero, as the heat absorption start boundary and heat absorption end boundary of the densification shrinkage stage. Within the interval formed by the heat absorption initiation boundary and the heat absorption termination boundary, an integral operation is performed on the densification characteristic curve to calculate the cumulative heat absorbed during the densification process, which is taken as the total energy consumption of the material reaction.

[0012] As a preferred embodiment of the automatic loading and unloading energy-saving production system for foamed ceramic insulation boards according to the present invention, the specific process of the calcination simulation module performing multi-dimensional variable calcination simulation based on the thermodynamic parameters includes: Construct a virtual thermal field environment that includes the physical boundaries of the main kiln and the spatial distribution characteristics of the green body stacking; The number of single-batch loading pieces is used as the spatial arrangement density variable, the calcination temperature is used as the external heat source input variable, and the shrinkage initiation temperature, the theoretical optimal heat absorption temperature, and the total energy consumption of the reaction are used as the target constraints of the material densification reaction and input into the virtual thermal field environment. Based on the spatial arrangement density variable, the kiln airflow obstruction effect and overall thermal inertia that increase with the number of green pieces are dynamically calculated, and the heat attenuation and time lag when external heat is conducted from the outer region of the batch to the geometric center region are deduced, so as to simulate and generate the actual temperature gradient curve of green pieces in different spatial positions within the same batch. in, This represents the effective heat transfer attenuation coefficient caused by spatial arrangement density; Indicates the number of wafers loaded in the current single batch; This indicates the maximum number of kiln cars that can be fully loaded within the physical space of the kiln car; The morphological drag coefficient representing the stacking of green bodies; The interference coefficient represents the penetration of hot air; This represents the cumulative heat actually absorbed by the green body in the geometric center region; This represents the preset system heat transfer coefficient; Indicates the quality of the green body; and These represent the time of the simulation. The kiln ambient temperature and the actual temperature of the central green body at that time; By combining the actual heating gradient curve derived from the theory with the optimal heat absorption temperature, the cumulative time required for the green blanks at each spatial location within the batch to complete the total energy consumption of the reaction is calculated; the amount of heat absorbed by the green blanks in the outer high-temperature region during the heat conduction waiting period is recorded simultaneously to determine the boundary overheating situation. After removing invalid variable combinations where the green body in the central region failed to reach the total energy consumption of the reaction and the green body in the outer region broke through the critical boundary of over-firing, the total time and total heat input consumed by the effective variable combinations in completing the densification reaction of the entire batch are extracted and used as the inferred time and inferred total energy consumption corresponding to each dynamic independent variable combination. The effective variable combinations are then correlated with the corresponding inferred time and inferred total energy consumption to construct a calcination inference mapping dataset.

[0013] As a preferred embodiment of the automatic loading and unloading energy-saving production system for foamed ceramic insulation boards described in this invention, the specific calculation process of the calcination optimization module includes: Obtain the calcination simulation mapping dataset output by the calcination simulation module, and construct a comprehensive benefit evaluation function that includes production capacity time weight and energy consumption cost weight; in, This represents the comprehensive benefit evaluation value corresponding to the combination of effective variables. This indicates the deduction time corresponding to this combination of variables; This represents the total energy consumption for the deduction corresponding to this combination of variables; and These represent the introduced normalized time reference constant and normalized energy consumption reference constant, respectively, used to eliminate the difference between the time dimension and the heat dimension; This represents the time-weighted coefficient for production capacity. This represents the energy consumption cost weighting coefficient; In the calcination simulation mapping dataset, the simulation time and total simulation energy consumption corresponding to the effective variable combination are respectively used as variables and substituted into the comprehensive benefit evaluation function to calculate the comprehensive benefit evaluation value corresponding to the effective variable combination. Extreme value optimization is performed on all comprehensive benefit evaluation values ​​to screen out the target extreme value point that represents the highest production energy efficiency ratio, and the effective variable combination corresponding to the target extreme value point is extracted; Based on the effective variable combination corresponding to the target extreme point, a preset redundancy amount for absorbing fluctuations in the actual industrial environment is superimposed to generate the theoretical optimal calcination parameters, which include the theoretical optimal calcination temperature, the number of wafers loaded in a single batch, and the processing time of a single batch.

[0014] As a preferred embodiment of the automatic loading and unloading energy-saving production system for foamed ceramic insulation boards described in this invention, the specific process of the fluid simulation module performing flow field simulation and deduction based on the theoretically optimal calcination parameters includes: The physical model of the double-layer convection heat exchange chamber is established: the structure includes a finished product cooling zone located below, a green preheating zone located above, heat transfer promotion equipment configured in the chamber, and a heat convection channel that naturally rises from the finished product cooling zone to the green preheating zone. Combining the pre-stored indoor capacity extreme value, the number of single-batch loaded pieces is used as the space occupancy benchmark and the single-batch processing time is used as the stepping beat. The total number of physical batches that can be accommodated in the double-layer convection heat exchange chamber is calculated, and the residence time of each batch at a specific cooling position and preheating position is derived. The flow field simulation is constrained in two ways: the finished product cooling zone is constrained to cool down to a safe furnace exit temperature within the residence time. In the high-temperature initial stage near the calcination end of the finished product cooling zone, the cooling rate of the finished product is limited to a preset critical upper limit for preventing thermal cracking. The green preheating zone is constrained to allow the green billet to absorb residual heat from below and reach a predetermined preheating target temperature within the residence time. The flow field is derived based on the constraints of the finished product cooling zone as the primary condition. After the baseline flow field state that meets the requirements of finished product cooling and thermal crack prevention is derived, the actual preheating temperature that the corresponding green billet can obtain is calculated. If the calculated actual preheating temperature does not reach the constraint of the green preheating zone, the simulated operating power of the heat transfer promotion equipment is gradually increased in the simulation model to enhance the heat exchange and transfer efficiency from bottom to top until the temperature states of the upper green and the lower finished product simultaneously meet the bidirectional constraint. Extract the required operating power and matching flow field state of the heat transfer promoting device that simultaneously satisfies the bidirectional constraints, and output them as effective air transport deduction parameters.

[0015] As a preferred embodiment of the automatic loading and unloading energy-saving production system for foamed ceramic insulation boards described in this invention, the specific calculation and screening process of the fluid optimization module includes: Obtain each set of effective air transport simulation parameters output by the fluid simulation module, and extract the required operating power corresponding to the heat transfer promotion equipment; Based on the determined equipment operating time in the double-layer convection heat exchange chamber, and based on the required operating power and the corresponding equipment operating time, the total energy consumption value of each set of effective air transport simulation parameters in a single operating cycle is obtained by direct summation calculation. All calculated total energy consumption values ​​are compared and optimized to select the optimal combination of deduced parameters with the lowest total energy consumption value as the low-energy-consumption air transmission implementation scheme.

[0016] As a preferred embodiment of the automatic loading and unloading energy-saving production system for foamed ceramic insulation boards described in this invention, the specific calculation and instruction generation process of the cold-state compensation calculation module includes: Define the cold transition time window of the system: take the first batch of green billets stepping into the green billet preheating zone above the double-layer convection heat exchange chamber as the starting node, and take the first batch of calcined high-temperature finished products stepping into the finished product cooling zone below, and take the residual heat released by them reaching the deduction benchmark of the air transmission implementation scheme as the ending node. Within the cold transition time window, the dynamic heat gap at each step is calculated by combining the theoretical heat absorption required for the green billet to reach the predetermined preheating target temperature with the air transmission implementation scheme, due to the complete absence of the bottom and only some high-temperature finished products. Based on the calculated dynamic heat gap, a corresponding initial external heat compensation command is generated. The initial external heat compensation command is configured as follows: at the starting node, the external auxiliary heat source is driven to output peak compensation heat, and within the cold transition time window, as the high-temperature finished products enter the finished product cooling zone in batches, the actual waste heat at the bottom layer rises, and the output power of the external auxiliary heat source is synchronously reduced according to the principle of heat equivalent replacement, until the termination node is reached and the waste heat circulation closed loop is completely formed, at which point the compensation action of the external auxiliary heat source is cut off.

[0017] As a preferred embodiment of the automatic loading and unloading energy-saving production system for foamed ceramic insulation boards described in this invention, the system further includes an auxiliary execution architecture for performing physical manufacturing and entity closed-loop feedback, specifically including: Multi-temperature zone physical execution module: configured to receive the theoretically optimal calcination parameters, the air transmission implementation scheme and the initial external heat compensation command, drive the heating action of the main kiln, promote the operation of the equipment through heat transfer in the double-layer convection heat exchange chamber, and control the opening and closing of the external auxiliary heat source according to a preset time sequence; Process deviation detection and dynamic evaluation module: After the system enters continuous production, the data acquisition module acquires the actual thermal state of each temperature zone in real time; when comparing the actual thermal state with theoretical parameters, a fault tolerance range that conforms to the logic of actual industrial operation is introduced to filter out normal equipment transient fluctuations; after detecting a substantial deviation beyond the fault tolerance range and a sudden drop in heat data that conforms to the laws of actual industrial physics, the actual heat difference is dynamically calculated and a corrected instantaneous heat compensation command is issued, based on the current physical position and remaining residence time of the batch that deviated in the kiln, to avoid finished product quality defects; Quality mapping and model evolution module: After the physical finished product leaves the kiln and completes physical performance testing, the test results are converted into weighted quality labels; the quality labels are associated with the corresponding batch's operation data and deviation intervention records throughout the entire process and archived to build a bottom-level entity training library; and the data in the entity training library is used to periodically back-calibrate the virtual thermal field environment in the calcination simulation module and fluid simulation module to complete the adaptive closed-loop evolution of the system.

[0018] The beneficial effects of this invention are as follows: by constructing a deduction mechanism based on real physical characteristics constraints and a multi-temperature zone dynamic closed-loop control architecture, the problems of excessively high energy consumption and local overheating caused by blindly setting parameters in traditional processes are solved. While maximizing the recovery and utilization of waste heat, the yield of the finished product of the whole furnace and the production energy efficiency ratio are significantly improved.

[0019] In the parameter derivation and optimization stage, the actual densification shrinkage initiation point and reaction energy consumption of the material are accurately extracted through pre-sintering tests. Based on this, the calcination simulation takes the airflow obstruction and heat retardation effect caused by green billet stacking as spatial constraints, effectively eliminates invalid schemes, and derives the theoretically optimal parameters that truly take into account both time and energy consumption limits.

[0020] In the thermal energy circulation process, a two-way forced temperature constraint is established by relying on the double-layer convection heat exchange chamber, which not only ensures the safe cooling and crack prevention of the finished product, but also realizes the efficient preheating of the green billet. During the cold start-up period of the system, based on the actual recovery state of the residual heat at the bottom layer, the external compensation power is precisely reduced according to the principle of equivalent heat replacement, eliminating the quality vacuum period and energy waste of the first batch of green billets.

[0021] During the physical operation phase, a fault tolerance range and an instant thermal compensation mechanism that conform to the physical logic of industry are introduced to effectively avoid single-batch defects. An adaptive closed loop is established from the finished product quality label to the virtual thermal field reverse calibration, enabling the system to continuously handle fluctuations in the production environment and maintain high accuracy and high industrial practical value of the optimization parameters in the long term. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a framework diagram of an automatic loading and unloading energy-saving production system for foamed ceramic insulation boards.

[0024] Figure 2 Flowchart for pre-sintering testing and calcination parameter optimization.

[0025] Figure 3 This is a flowchart of the flow field simulation and cold-state compensation for a double-layer heat exchanger.

[0026] Figure 4 This is a flowchart of process deviation checking and adaptive model evolution. Detailed Implementation

[0027] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0028] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0029] Secondly, the term "one embodiment" or "example" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the invention. The appearance of an embodiment in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that mutually excludes other embodiments.

[0030] Example 1 Reference Figures 1-4 As one embodiment of the present invention, this embodiment provides an automatic loading and unloading energy-saving production system for foamed ceramic insulation boards, comprising the following modules: Thermodynamic benchmark testing module: used to perform pre-sintering tests. The pre-sintering process is controlled by the gradient temperature control module. During the process, the data acquisition module continuously records the pre-sintering parameters, and the thermodynamic parameter calculation module calculates the thermodynamic parameters of the material by analyzing the pre-sintering parameters. The specific operations of the gradient temperature control module in controlling the pre-sintering process include: The starting temperature reference for the pre-sintering environment is set based on the temperature at which a thermochemical reaction is determined to be non-existent. Starting from the initial temperature reference, the temperature is increased in a stepped manner, alternating between a preset temperature increase and a fixed holding time. During the execution of the stepped heating action, real-time monitoring data fed back by the data acquisition module is received synchronously; after a significant initial curve shift indicating the reaction inside the material is detected in the feedback data, the current heating rate is maintained, the heat preservation step in the stepped heating action is skipped, until the shift process ends and the temperature returns to the normal physical heating baseline state, and the stepped heating action is resumed. The process of repeating the response curve shift to switch the heating mode continues until the last data shift state characterizing the densification shrinkage process is detected, at which point the pre-sintering test is terminated. The data acquisition module is configured to continuously acquire multi-dimensional sensor data throughout the system's pre-sintering test and actual production cycle. Specific acquisition operations include: The optical volume change data of the green body during the heating process are collected by a laser profile sensor installed at the high-temperature observation window of the main kiln. The actual ambient temperature of the kiln and the actual temperature of the green body are collected by thermocouples arranged on the inner wall of the main kiln and infrared radiation thermometers that are non-contact and aligned with the surface of the green body. The actual preheating temperature of the upper preheating zone and the actual cooling temperature of the lower cooling zone are collected by a sensor network deployed in the double-layer convection heat exchange chamber. The specific calculation process of the thermodynamic parameter calculation module includes: By combining the optical volume change data of the green body with the actual temperature of the green body, the starting point of the last data shift, which represents the continuous shrinkage of the volume, is identified after the green body undergoes an initial expansion shift due to heating and returns to a stable state. The actual temperature of the green body corresponding to the starting point of the last data shift is extracted as the shrinkage initiation temperature of the material. The dynamic temperature difference between the actual ambient temperature of the kiln and the actual temperature of the green body is calculated, and the original heat absorption curve reflecting the entire heating process is generated. The original heat absorption curve is then smoothed to obtain a smoothed heat absorption curve. The segment corresponding to the last data shift process in the smooth thermal absorption curve is selected as the densification characteristic curve. The first derivative of the densification characteristic curve is calculated to find the extreme point of the theoretical optimal heat absorption temperature characterizing the material during the densification process, and the temperature corresponding to the extreme point is taken as the theoretical optimal heat absorption temperature. The second derivative of the densification characteristic curve is calculated, and two adjacent inflection points where the second derivative value is equal to zero are extracted as the heat absorption start boundary and heat absorption end boundary of the densification shrinkage stage. Within the interval formed by the endothermic initiation boundary and the endothermic termination boundary, an integral operation is performed on the densification characteristic curve to calculate the cumulative heat absorbed during the densification process, which is taken as the total energy consumption of the material reaction.

[0031] The pre-sintering test process officially begins after the system receives the test instruction for a new batch of green blanks. The system first calls the pre-stored material property database based on the input foamed ceramic formula information, extracts the critical temperature at which the formula undergoes only physical thermal expansion in the initial stage of heating and is determined not to undergo thermochemical reactions, and sets this temperature as the starting temperature reference for the pre-sintering environment.

[0032] Starting from this initial temperature reference, the gradient temperature control module drives the main kiln into an alternating, stepped heating mode. The system heats up according to a preset temperature increase, followed by a fixed holding time. This alternating heating and holding logic aims to provide sufficient heat conduction time for the green body with a certain thickness, ensuring that the temperature of its internal core and external surface reaches equilibrium during the holding period, thereby eliminating testing errors caused by internal and external temperature differences.

[0033] During this period, the data acquisition module continuously operates in a high-frequency sampling state. The laser contour sensor installed at the high-temperature observation window of the main kiln projects a structured light array onto the surface of the green billet, capturing and reconstructing the three-dimensional contour of the green billet in real time, thereby outputting high-precision optical volume change data; at the same time, the thermocouples and infrared radiation thermometers on the side walls output the actual ambient temperature of the kiln and the actual temperature of the green billet in real time, respectively.

[0034] As the temperature increases, when a significant initial curve shift, characteristic of the internal reaction of the material, appears in the real-time monitoring data fed back by the data acquisition module (e.g., the actual temperature rise rate of the green blank lags significantly behind the ambient temperature, exhibiting obvious endothermic stagnation), the system determines that the reaction has been triggered. The system will interrupt the heat preservation phase in the stepped heating process and maintain the current heating rate for continuous heating. This intervention is to maintain stable external thermodynamics during the active phase of the material reaction, fully capturing the continuous kinetic characteristics of the reaction process. The system resumes the alternating heating and heat preservation process only after the data shift ends and the temperature change rate returns to the normal physical heating baseline. This response curve shift is repeated cyclically with the switching heating modes until the laser profile sensor detects a drastic densification shrinkage process in the green blank volume, and the final data shift state ends. At this point, the system determines that the thermodynamic evolution is complete, thus terminating the pre-sintering test.

[0035] Subsequently, the thermodynamic parameter calculation module began to perform in-depth analysis of the multidimensional sensing data.

[0036] First, the optical volume change data after time axis alignment was correlated with the actual green body temperature. Through morphological analysis, the starting point of the last data offset, which represents the continuous and significant shrinkage of the green body volume, was extracted, and the actual green body temperature corresponding to this starting point was extracted and established as the shrinkage initiation temperature of the material.

[0037] The system calculates the dynamic temperature difference between the actual ambient temperature of the kiln and the actual temperature of the green body according to a time series, generating an original heat absorption curve reflecting the entire heating process. When smoothing this original curve to eliminate sensor electrical noise, the system employs a locally weighted filtering algorithm with physical feature preservation weights. This ensures that the curve accurately reflects reasonable fluctuations and sudden drops in heat data present in actual industrial performance logic, avoiding overfitting it to a purely theoretical smooth curve that would lose core physical characteristics. This results in a high-fidelity, smooth heat absorption curve being output.

[0038] The system further extracts a segment from the smooth thermal absorption curve that completely overlaps with the time axis of the aforementioned final data offset process, and defines it as the densification characteristic curve.

[0039] To find the optimal energy injection point, the system performs first-order derivative calculations on the densification characteristic curve to solve for the gradient of the heat absorption rate. By traversing the calculation results, the system searches for the maximum point where the derivative value is zero and changes from positive to negative in its neighborhood. This extreme point represents the time when the material absorbs heat most intensely during densification. The system extracts the actual green body temperature corresponding to this extreme point and establishes it as the theoretically optimal heat absorption temperature.

[0040] To clarify the thermal boundaries of the entire densification stage, the system continues to perform second derivative calculations on the densification characteristic curve. The system extracts two adjacent inflection points on the curve where the second derivative value equals zero. These two inflection points characterize the critical points where the densification reaction transitions from the latent phase to the accelerated endothermic phase, and from the endothermic peak to the decline phase, respectively. The system uses the time points corresponding to these two inflection points as the endothermic start and end boundaries of the densification contraction phase, respectively.

[0041] in, This represents the total energy consumed by the reaction accumulated during the entire densification process of the material. and These represent the endothermic initiation boundary time and endothermic termination boundary time, respectively, determined by the second derivative of the densification characteristic curve. This represents the preset system heat transfer coefficient; Indicates the quality of the green body; Represents any moment within the integration time interval. The dynamic temperature difference between the actual ambient temperature of the kiln and the actual temperature of the green body is obtained in real time by sensors.

[0042] Within the effective reaction range defined by the endothermic initiation and termination boundaries, the system, combining the preset system heat transfer coefficient and green body mass, performs definite integral calculations on the densification characteristic curve to quantify the actual heat absorbed by the material during the entire densification process, and establishes this value as the total energy consumption of the material's reaction. At this point, the set of realistic thermodynamic parameters is complete, providing a benchmark for subsequent calcination simulations.

[0043] Calcination parameter optimization module: The calcination simulation module performs multi-dimensional calcination simulation based on thermodynamic parameters, and the calcination optimization module calculates the theoretical optimal calcination parameters, including the number of loaded pieces per batch and the processing time per batch, based on the calcination simulation results. The specific process of the calcination simulation module performing multidimensional variable calcination simulation based on thermodynamic parameters includes: Construct a virtual thermal field environment that includes the physical boundaries of the main kiln and the spatial distribution characteristics of the green body stacking; The number of single-batch loading pieces is used as the spatial arrangement density variable, the calcination temperature is used as the external heat source input variable, and the shrinkage initiation temperature, theoretical optimal heat absorption temperature, and total reaction energy consumption are used as target constraints for the material densification reaction and input into the virtual thermal field environment. Based on the spatial arrangement density variable, the kiln airflow obstruction effect and overall thermal inertia that increase with the number of green pieces are dynamically calculated. The heat attenuation and time lag when external heat is conducted from the outer region of the batch to the geometric center region are deduced, so as to simulate and generate the actual temperature gradient curve of green pieces in different spatial positions within the same batch. By combining the actual heating gradient curve derived from the theoretical optimal heat absorption temperature, the cumulative time required for the green body at each spatial location within the batch to complete the total energy consumption of the reaction is calculated; the amount of heat absorbed by the green body in the outer high-temperature region during the heat conduction waiting period is recorded simultaneously to determine the boundary overheating situation. After removing invalid variable combinations where the green body in the central region failed to reach the total energy consumption of the reaction and the green body in the outer region broke through the critical boundary of over-firing, the total time and total heat input consumed by the effective variable combinations in completing the densification reaction of the whole batch were extracted and used as the inferred time and inferred total energy consumption corresponding to each dynamic independent variable combination. The effective variable combinations were correlated with the corresponding inferred time and inferred total energy consumption to construct a calcination inference mapping dataset. The specific calculation process of the calcination optimization module includes: Obtain the calcination simulation mapping dataset output by the calcination simulation module, and construct a comprehensive benefit evaluation function that includes production capacity time weight and energy consumption cost weight; In the calcination simulation mapping dataset, the simulation time and total energy consumption corresponding to the effective variable combination are respectively used as variables and substituted into the comprehensive benefit evaluation function to calculate the comprehensive benefit evaluation value corresponding to the effective variable combination. Extreme value optimization is performed on all comprehensive benefit evaluation values ​​to screen out the target extreme value point that represents the highest production energy efficiency ratio, and the effective variable combination corresponding to the target extreme value point is extracted; Based on the effective combination of variables corresponding to the target extreme point, a preset redundancy amount for absorbing fluctuations in the actual industrial environment is superimposed to generate theoretically optimal calcination parameters, including the theoretical optimal calcination temperature, the number of wafers loaded in a single batch, and the processing time in a single batch.

[0044] After obtaining the thermodynamic parameters including the shrinkage initiation temperature, the theoretical optimal heat absorption temperature, and the total energy consumption of the reaction, the calcination simulation module initiates the virtual simulation process. The system first constructs a virtual thermal field environment containing the absolute physical boundaries of the main kiln in the virtual computing environment, based on the actual engineering drawings and three-dimensional dimensions of the main kiln. Simultaneously, the gridded placement and hierarchical structure of the green billets on the kiln car are mapped to the spatial distribution characteristics within this virtual thermal field environment.

[0045] The system performs multidimensional variable loading and boundary constraint setting. The number of wafers loaded in a single batch is used as the independent variable affecting the spatial arrangement density of the thermal field, and different calcination temperatures are set as independent variables for external heat source input. At the same time, the above-mentioned extracted thermodynamic parameters are used as physical target constraints for the material densification reaction and input into the constructed virtual thermal field environment.

[0046] During the simulation phase, the system dynamically calculates the kiln airflow obstruction effect caused by the increase in the number of green pieces and the compression of physical airflow channels, based on the spatial arrangement density variable of the current loading. Simultaneously, it quantifies the overall thermal inertia of the entire loading batch, which increases non-linearly. Based on this, the system simulates the actual heat attenuation and time lag as external heat penetrates and conducts from the outer region of the batch to the geometric center. When simulating the actual temperature gradient curves of green pieces at different spatial locations within the same batch, the simulation process strictly follows the thermodynamic laws of actual industrial operation, fully considering reasonable fluctuations in heat flow conduction under real-world conditions and the sudden drop in localized heat caused by obstruction, thus avoiding parameter distortion caused by purely theoretical smoothing fitting.

[0047] in, This represents the effective heat transfer attenuation coefficient caused by spatial arrangement density; Indicates the number of wafers loaded in the current single batch; This indicates the maximum number of kiln cars that can be fully loaded within the physical space of the kiln car; The morphological drag coefficient representing the stacking of green blanks (reflecting the frictional obstruction of airflow by the surface texture and stacking gaps of the green blanks; a reference value can be found at...) ); The interference coefficient representing the penetration of hot air (a reference value can be used). ), using natural logarithm The function is designed to realistically fit the nonlinear physical law in industrial settings where, as the loading density approaches its limit, the heat flow channel is drastically compressed, leading to a sharp drop in heat transfer efficiency.

[0048] This represents the cumulative heat actually absorbed by the green body in the geometric center region; This represents the system heat transfer coefficient presupposed in the preceding text; Indicates the quality of the green body; and These represent the time of the simulation. The ambient temperature of the kiln and the actual temperature of the central green body at that time.

[0049] Based on this, the system combines the derived actual heating gradient curve with the theoretical optimal heat absorption temperature, and performs tracking calculations on the time axis to obtain the cumulative time required for the green bodies at different spatial locations within the batch to complete the total reaction energy consumption. While waiting for the green bodies in the central region to reach the total reaction energy consumption, the system synchronously and continuously records the additional heat absorption of the green bodies in the outer high-temperature direct-heat zone, and compares this cumulative absorption with the structural collapse heat threshold of foamed ceramics, thus serving as the physical basis for judging the boundary overfiring situation.

[0050] After a single batch of multidimensional simulations is completed, the system enters the invalid data removal and dataset mapping stage. For variable combinations where the simulation results show that the green billet in the central region fails to reach the total energy consumption of the reaction due to heat conduction attenuation, and for variable combinations where the green billet in the outer region exceeds the critical overheating boundary due to excessive heat transfer waiting time, the system classifies them as invalid schemes and removes them directly. For the remaining valid variable combinations after filtering, the system extracts the total time and total heat input required to complete the densification reaction for the entire batch, defining them as the projected time and projected total energy consumption corresponding to that dynamic independent variable combination. Subsequently, the system correlates all valid variable combinations with their corresponding projected time and projected total energy consumption to construct a structured calcination projection mapping dataset.

[0051] The calcination optimization module then calls the calcination simulation mapping dataset to perform extreme value optimization. The system first constructs a comprehensive benefit evaluation function, which incorporates a pre-set capacity time weight based on the industrial production schedule and a pre-set energy cost weight based on the energy unit price. The system uses the simulation time and total simulation energy consumption corresponding to each effective variable combination in the dataset as input variables, substitutes them into the comprehensive benefit evaluation function, and calculates the comprehensive benefit evaluation value for each combination.

[0052] in, This represents the comprehensive benefit evaluation value corresponding to the combination of effective variables (the smaller the value, the lower the comprehensive production cost and the highest energy efficiency ratio). This indicates the deduction time corresponding to this combination of variables; This represents the total energy consumption for the deduction corresponding to this combination of variables; and These represent the introduced normalized time reference constant and normalized energy consumption reference constant, respectively, used to eliminate the difference between the time dimension and the heat dimension; This represents the time-weighted coefficient for production capacity. This represents the energy consumption cost weighting coefficient, and satisfies... In practical industrial applications, and The value can be dynamically adjusted according to the factory's current production scheduling pressure. For example, in a state of urgent orders, the time weight can be increased (e.g., ...). During normal, stable production periods, to achieve maximum energy savings, the energy consumption weight can be increased (reference value). ).

[0053] By performing a global traversal search on all comprehensive benefit evaluation values, the target extreme point that can represent the highest production energy efficiency ratio (i.e. the optimal solution after the game between time cost and energy consumption cost) is selected, and the effective variable combination corresponding to the target extreme point is extracted.

[0054] Based on the effective variable combination corresponding to the target extreme point, the system superimposes a preset physical redundancy to absorb fluctuations in the actual industrial environment (such as transient deviations in grid voltage and heat loss caused by the natural aging of kiln insulation materials). After redundancy superposition and correction, the system finally generates theoretically optimal calcination parameters, including the theoretical optimal calcination temperature, the number of pieces loaded per batch, and the processing time per batch.

[0055] Heat exchange fluid simulation module: The fluid simulation module performs flow field simulation and deduction on the double-layer convection heat exchange chamber based on the number of loaded plates in a single batch, the processing time of a single batch, and the bidirectional temperature constraint. The fluid optimization module selects low-energy air transmission implementation schemes based on the flow field simulation and deduction results. The specific process of flow field simulation and deduction based on theoretically optimal calcination parameters in the fluid simulation module includes: The physical model of the double-layer convection heat exchange chamber is established: the structure includes the finished product cooling zone at the bottom, the green preheating zone at the top, the heat transfer promotion equipment configured in the chamber, and the heat convection channel that rises naturally from the finished product cooling zone to the green preheating zone. By combining the pre-stored indoor capacity extreme value, using the number of single-batch loaded pieces as the space occupancy benchmark and the single-batch processing time as the stepping beat, the total number of physical batches that can be accommodated in the double-layer convection heat exchange chamber is calculated, and the residence time of each batch at a specific cooling position and preheating position is derived. Two-way constraints are set for flow field simulation: the finished product cooling zone constraint is that the finished product cools down to the safe furnace exit temperature within the residence time. In the high-temperature initial stage near the calcination end of the finished product cooling zone, the cooling rate of the finished product is limited to the preset critical upper limit for preventing thermal cracking; the green preheating zone constraint is that the green billet absorbs the residual heat below and reaches the predetermined preheating target temperature within the residence time. The flow field is derived based on the constraint of the finished product cooling zone as the primary condition. After deriving the benchmark flow field state that meets the requirements of finished product cooling and thermal crack prevention, the actual preheating temperature that the corresponding green billet can obtain is calculated. If the calculated actual preheating temperature does not reach the preheating zone constraint of the green billet, the simulated operating power of the heat transfer promotion equipment is gradually increased in the simulation model to enhance the heat exchange efficiency from bottom to top until the temperature states of the upper green billet and the lower finished product simultaneously meet the bidirectional constraint. Extract the required operating power and matching flow field state of the heat transfer promoting equipment that simultaneously satisfy the bidirectional constraints, and output them as effective air transfer simulation parameters. The specific calculation and screening process of the fluid optimization module includes: Obtain each set of effective air transport simulation parameters output by the fluid simulation module, and extract the required operating power corresponding to the heat transfer promotion equipment; Based on the determined equipment operating time in the double-layer convection heat exchange chamber, and based on the required operating power and the corresponding equipment operating time, the total energy consumption value of each set of effective air transfer simulation parameters in a single operating cycle is obtained by direct summation calculation. All calculated total energy consumption values ​​are compared and optimized to select the optimal combination of deduced parameters with the lowest total energy consumption value as the low-energy-consumption air transmission implementation scheme.

[0056] After obtaining the theoretically optimal calcination parameters, the fluid simulation module initiates a simulation process for the double-layer convection heat exchanger. The system first establishes the physical simulation architecture of the double-layer convection heat exchanger in a virtual computing environment. This architecture strictly maps the physical space of the actual equipment, specifically including: the finished product cooling zone below, the green preheating zone above, heat transfer promoting equipment configured within the chamber (such as variable frequency circulating fans and guide vanes), and the naturally rising heat convection channels from the finished product cooling zone to the green preheating zone.

[0057] Subsequently, the system performs calculations and mapping of the spatiotemporal reference. The system calls upon pre-stored extreme values ​​of the heat exchange chamber capacity, using the number of load pieces per batch in the theoretically optimal calcination parameters as the spatial occupancy reference, and the processing time per batch as the stepping frequency of the conveying system. Through a division conversion between space and frequency, the total number of physical batches that can be simultaneously accommodated in the double-layer convection heat exchange chamber is calculated, and from this, the absolute residence time of each batch at specific cooling and preheating positions is derived.

[0058] Before the formal operation of the simulation, the system sets two-way forced physical constraints for the flow field simulation. The first is the finished product cooling zone constraint (bottom constraint), which requires that the finished product must be cooled to a safe furnace exit temperature that allows it to safely contact the environment within the absolute residence time. At the same time, for the finished product that has just entered the finished product cooling zone from the main kiln and is in the high-temperature initial stage near the calcination end, the system strictly limits its cooling rate to a preset critical upper limit for preventing thermal cracking, in order to avoid drastic temperature changes that could cause stress imbalance and cracking of the ceramic. The second is the green body preheating zone constraint (top constraint), which forces the green body to fully absorb the rising residual heat below within the same absolute residence time and reach the predetermined preheating target temperature.

[0059] After entering the dynamic flow field simulation stage, the system first performs a basic flow field simulation based on the constraint of the finished product cooling zone. After deriving the baseline flow field state that precisely meets the requirements for finished product cooling and thermal crack prevention based on natural thermal convection, the system traces back to calculate the actual preheating temperature that the upper green billet can obtain under the natural flow field state at this time.

[0060] If the calculated actual preheating temperature fails to meet the constraints of the green billet preheating zone, the system determines that the natural convection heat transfer capacity is insufficient. The system then executes a step-by-step increase in heat transfer efficiency within the simulation model to enhance the simulated operating power of the equipment. This improves the bottom-up heat exchange efficiency and provides real-time feedback to the temperature models of both the upper and lower zones. This cyclical process of gradual improvement and verification continues until the preheating temperature of the upper green billet and the cooling state of the lower finished product simultaneously satisfy the bidirectional forced constraints.

[0061] The system extracts the required operating power of the heat transfer promoting equipment and the flow field distribution state that perfectly matches it when the two-way constraint is satisfied, and outputs them as effective air transfer simulation parameters.

[0062] The fluid optimization module then takes over the data flow, performing energy consumption calculations and scheme selection. The system acquires all valid air transport simulation parameter combinations output by the fluid simulation module and extracts the required operating power for heat transfer-promoting equipment.

[0063] Combining the determined equipment operating time within the double-layer convection heat exchange chamber, which is limited by the step cycle, the system calculates the total energy consumption of each set of effective air transport simulation parameters within a single complete operating cycle through direct physical addition and multiplication operations based on the extracted required operating power and the equipment operating time.

[0064] The system performs a one-dimensional comparison and optimization of all calculated total energy consumption values, selecting the optimal combination of deduced parameters with the lowest total energy consumption. This optimal combination of deduced parameters is then directly established as the low-energy-consumption air transmission implementation scheme to guide the operation of physical equipment.

[0065] Cold state compensation calculation module: Based on the air transmission implementation scheme, calculate the heat gap of the first batch of green billets before the formation of the waste heat circulation closed loop in the double-layer convection heat exchange chamber, and generate the corresponding initial external heat compensation command. The specific calculation and instruction generation process of the cold compensation calculation module includes: Define the cold transition time window of the system: take the first batch of green billets stepping into the green billet preheating zone above the double-layer convection heat exchange chamber as the starting node, and take the first batch of calcined high-temperature finished products stepping into the finished product cooling zone below, and take the released residual heat reaching the deduction benchmark of the air transmission implementation scheme as the ending node. Within the cold transition time window, combining the theoretical heat absorption and air transfer scheme required for the green billet to reach the predetermined preheating target temperature, the dynamic heat gap under each step is calculated due to the complete absence of the bottom and only some high-temperature finished products. Based on the calculated dynamic heat gap, the corresponding initial external heat compensation command is generated. The initial external heat compensation command is configured as follows: at the starting node, the external auxiliary heat source is driven to output peak compensation heat. During the cold transition time window, as the high-temperature finished products enter the finished product cooling zone in batches and the actual waste heat at the bottom layer rises, the output power of the external auxiliary heat source is reduced synchronously according to the principle of heat equivalent replacement. When the termination node is reached and the waste heat circulation loop is fully formed, the compensation action of the external auxiliary heat source is cut off.

[0066] During the initial system startup or restart after a prolonged shutdown, the main kiln and the double-layer convection heat exchanger are in a cold state, lacking internal circulating heat. At this time, the cold-state compensation calculation module is activated, first defining the system's cold-state transition time window. The system establishes the trigger time of the mechanical transmission device pushing the first batch of green billets into the green billet preheating zone above the double-layer convection heat exchanger as the starting node of this time window. Subsequently, as the production line continues to operate, the first batch of high-temperature finished products, having completed the entire calcination process in the main kiln, exits the kiln and is pushed into the finished product cooling zone below by the stepper motor. The system continuously monitors the bottom thermal field, and when the residual heat released by the bottom finished products first reaches the projection benchmark required by the aforementioned effective air transfer implementation scheme, the system establishes this as the termination node. The entire physical time span from the starting node to the termination node is strictly defined as the cold-state transition time window.

[0067] Within the aforementioned cold transition time window, the system performs high-frequency dynamic heat gap calculations. At the initial stage, the heat source at the bottom layer of the heat exchange chamber is completely absent; and during the subsequent transition period, only some high-temperature finished products gradually enter from below, failing to provide sufficient natural heat convection. The system, combining the theoretical total heat required for the green billet to reach the predetermined preheating target temperature with the preset air transfer implementation scheme, calculates the difference between the heat demand of the upper green billet and the actual available residual heat below in step-by-step cycle time, thereby outputting a dynamic heat gap curve that varies with the cycle time.

[0068] in, This indicates that within the cold transition time window, the first... Dynamic heat gap under each step beat; This represents the theoretical total heat absorbed by a single batch of green billets to reach a predetermined preheating target temperature. Indicates that during the execution of the first During each step cycle, the total number of high-temperature finished product batches currently contained in the finished product cooling zone below (when... That is, at the starting node, ); Indicates the number of products entering the finished product cooling zone The effective physical residual heat that can be released by a batch of high-temperature finished products; Indicates the first At each step, the system issues the output power command value to the external auxiliary heat source; It represents the absolute physical time lasting for a single step beat; This represents the thermal conversion efficiency of an external auxiliary heat source in converting consumed electrical energy or gas chemical energy into convective heat energy. This coefficient is affected by the insulation performance of the heat exchange chamber and the degree of aging of the heater. The usable reference value under normal operating conditions is [value missing]. .

[0069] Based on the calculated dynamic heat gap curve, the cold state compensation calculation module directly compiles and generates the corresponding initial external heat compensation instruction, and sends the instruction to the auxiliary execution architecture.

[0070] When the starting node is triggered, the dynamic heat gap is at its maximum. The command directly drives the external auxiliary heat source to operate at full load, outputting peak compensation heat to the green billet preheating zone to ensure that the first batch of green billets will not have quality defects due to insufficient preheating. After entering the cold transition time window, as the high-temperature finished products enter the finished product cooling zone batch by batch with the stepping rhythm, the actual physical waste heat released at the bottom begins to rise in stages. At this time, the command performs dynamic adjustment according to the principle of equivalent heat substitution: for every additional unit of physical waste heat at the bottom, the system synchronously and proportionally reduces the output power of the external auxiliary heat source. This synchronous reduction action continues throughout the entire transition period until the time axis reaches the termination node. At this time, the waste heat circulation closed loop of the upper and lower layers has been fully formed and has self-sustaining capability. The system immediately cuts off all compensation actions of the external auxiliary heat source, and officially smoothly transitions the system to a low-energy-consumption operation mode driven by pure physical waste heat.

[0071] The system also includes an auxiliary execution architecture for performing physical manufacturing and physical closed-loop feedback, specifically including: Multi-temperature zone physical execution module: configured to receive theoretically optimal calcination parameters, air transmission implementation scheme and initial external heat compensation command, drive the heating action of the main kiln, promote the operation of the equipment through heat transfer in the double-layer convection heat exchange chamber, and control the opening and closing of the external auxiliary heat source according to the preset time sequence. Process deviation detection and dynamic evaluation module: After the system enters continuous production, it is configured to acquire the actual thermal state of each temperature zone in real time through the data acquisition module; when comparing the actual thermal state with theoretical parameters, a fault tolerance range that conforms to the logic of actual industrial operation is introduced to filter out normal transient fluctuations in equipment; after detecting substantial deviations exceeding the fault tolerance range and sudden drops in heat data that conform to the laws of actual industrial physics, the actual heat difference is dynamically calculated and a corrected real-time heat compensation command is issued, based on the current physical position and remaining residence time of the batch that deviated in the kiln, to avoid defects in finished product quality; Quality Mapping and Model Evolution Module: After the physical finished product leaves the kiln and completes physical performance testing, the test results are converted into weighted quality labels; the quality labels are associated with the corresponding batch's operational data and deviation intervention records throughout the entire process and archived to build a bottom-level entity training library; and the data in the entity training library is used to periodically back-calibrate the virtual thermal field environment in the calcination simulation module and fluid simulation module to complete the adaptive closed-loop evolution of the system.

[0072] After the virtual model completes all preliminary simulations and generates final control commands, the system enters the physical manufacturing stage. The multi-temperature zone physical execution module intervenes first, acting as the central hub connecting digital commands and physical equipment. This module analyzes the received theoretically optimal calcination parameters, effective air transmission implementation schemes, and initial external heat compensation commands, converting them into underlying equipment drive electrical signals. Subsequently, this module drives the gas proportional valves or electric heating elements in each temperature zone of the main kiln to perform heating actions according to the set power, simultaneously driving the heat transfer promotion equipment (such as variable frequency fans) in the double-layer convection heat exchange chamber to reach the required speed, and strictly controlling the opening and closing of external auxiliary heat sources according to preset timing and decay curves, thereby establishing a physical thermal field that conforms to theoretical simulations.

[0073] Once the system enters continuous production mode, the process deviation detection and dynamic evaluation module initiates high-frequency background monitoring. This module continuously and in real-time acquires the actual thermal operating conditions of each temperature zone through the data acquisition module. It provides this information while comparing the actual thermal operating conditions with theoretically derived parameters frame by frame. By introducing a fault-tolerant range that conforms to the physical logic of actual industrial operation, it identifies and automatically filters out routine data spikes caused by minor fluctuations in grid power, normal transient vibrations of equipment, or brief electrical noise from sensors, thus preventing the system from frequently triggering false alarms or excessive intervention due to normal industrial fluctuations.

[0074] When monitoring data continuously exceeds the tolerance boundary, resulting in a substantial deviation beyond the tolerance range, or when a sudden drop in heat data consistent with actual industrial physics is identified, the system immediately triggers a dynamic deviation detection and intervention mechanism. First, physical tracing is performed in the digital space to precisely pinpoint the specific batch of green billets affected by the heat drop, and the current coordinates of that batch within the kiln's physical space, along with its remaining residence time before exiting the kiln, are extracted. Based on these spatial and temporal variables, the actual heat difference required for the batch to achieve complete densification is quickly calculated, and a targeted, immediate heat compensation command is issued. This command drives the nearest local compensation heating element to perform targeted heat recovery within the remaining residence time, thereby minimizing the quality defects in the finished product caused by localized underfiring in a single batch without disrupting the overall production line's operating rhythm.

[0075] in, This represents the actual heat difference accumulated from the time of the sudden drop in heat to the current moment; This indicates the initial moment when the system detected a sudden drop in heat data that exceeded the fault tolerance range; Indicates the current time of the offset calculation; This represents the theoretical temperature that should be reached at this moment, derived from the theoretically optimal calcination parameters; This indicates the actual temperature drop measured by the sensor. This indicates the immediate thermal compensation power command issued to the local heating element; This indicates the remaining absolute residence time of the batch of green blanks that deviated from the target in the main kiln. This indicates the electrothermal conversion efficiency of a locally compensated heating element (such as the actual efficiency of a silicon carbide heating rod after attenuation; a reference value can be used). ); This represents the environmental heat loss penalty coefficient under sudden temperature drop conditions, used to compensate for the additional heat dissipation after the local thermal field of the kiln is disrupted (a reference value can be used). ).

[0076] Once the finished product completes the entire processing and exits the kiln, the quality mapping and model evolution module takes over the final stage of closed-loop optimization. The system acquires real physical inspection data for each batch of finished products in the physical performance testing section (such as compressive strength testing and thermal conductivity measuring instrument), and transforms these discrete test results into weighted standard quality labels.

[0077] After label conversion, the system performs deep feature binding and data archiving. The system maps and deeply associates the quality label with all real operational data of that specific batch throughout the entire process (including the original temperature rise curve, residence time, whether there was a sudden drop in heat and the corresponding intervention records). This structured, multi-dimensional associated data is packaged uniformly and continuously stored in the system's underlying entity training library.

[0078] The system is designed with a regular evolution cycle. After reaching a preset data accumulation amount or time period, the system extracts macroscopic pattern data from the underlying entity training library and compares it against preset physical constraint parameters in the virtual thermal field environment. By identifying systematic minor deviations between theoretical deduction and the final entity quality, the system automatically fine-tunes core underlying parameters such as airflow resistance coefficient and thermal inertia transfer attenuation rate in the calcination simulation module and fluid simulation module, completing the reverse calibration of the virtual thermal field environment. This adaptive closed-loop evolution mechanism, which accompanies the continuous production process, allows the system to continuously absorb and digest long-term physical fluctuations in the actual production environment, thereby ensuring that the theoretically optimal parameters output by the system maintain extremely high accuracy and industrial practical value throughout its long lifecycle.

[0079] In summary, by constructing a deduction mechanism based on real physical characteristics constraints and a multi-temperature zone dynamic closed-loop control architecture, the problems of excessively high energy consumption and local overheating caused by blindly setting parameters in traditional processes have been solved. While maximizing the recovery and utilization of waste heat, the yield of the finished product and the production energy efficiency ratio of the entire furnace have been significantly improved.

[0080] In the parameter derivation and optimization stage, the actual densification shrinkage initiation point and reaction energy consumption of the material are accurately extracted through pre-sintering tests. Based on this, the calcination simulation takes the airflow obstruction and heat retardation effect caused by green billet stacking as spatial constraints, effectively eliminates invalid schemes, and derives the theoretically optimal parameters that truly take into account both time and energy consumption limits.

[0081] In the thermal energy circulation process, a two-way forced temperature constraint is established by relying on the double-layer convection heat exchange chamber, which not only ensures the safe cooling and crack prevention of the finished product, but also realizes the efficient preheating of the green billet. During the cold start-up period of the system, based on the actual recovery state of the residual heat at the bottom layer, the external compensation power is precisely reduced according to the principle of equivalent heat replacement, eliminating the quality vacuum period and energy waste of the first batch of green billets.

[0082] During the physical operation phase, a fault tolerance range and an instant thermal compensation mechanism that conform to the physical logic of industry are introduced to effectively avoid single-batch defects. An adaptive closed loop is established from the finished product quality label to the virtual thermal field reverse calibration, enabling the system to continuously handle fluctuations in the production environment and maintain high accuracy and high industrial practical value of the optimization parameters in the long term.

[0083] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An automatic loading and unloading energy-saving production system for foamed ceramic insulation boards, characterized in that, Executed by computer equipment, including the following modules: Thermodynamic benchmark testing module: used to perform pre-sintering tests. The pre-sintering process is controlled by the gradient temperature control module. During the process, the data acquisition module continuously records the pre-sintering parameters, and the thermodynamic parameter calculation module calculates the thermodynamic parameters of the material by analyzing the pre-sintering parameters. Calcination parameter optimization module: The calcination simulation module performs multi-dimensional variable calcination simulation based on the thermodynamic parameters, and the calcination optimization module calculates the theoretical optimal calcination parameters, including the number of loaded pieces per batch and the processing time per batch, based on the calcination simulation results. Heat exchange fluid simulation module: The fluid simulation module performs flow field simulation and deduction on the double-layer convection heat exchange chamber based on the number of single-batch loading plates, the single-batch processing time, and bidirectional temperature constraints. The fluid optimization module selects low-energy-consumption air transmission implementation schemes based on the flow field simulation and deduction results. Cold state compensation calculation module: Based on the air transmission implementation scheme, calculate the heat gap of the first batch of green billets before the formation of the waste heat circulation closed loop in the double-layer convection heat exchange chamber, and generate the corresponding initial external heat compensation command.

2. The automatic loading and unloading energy-saving production system for foamed ceramic insulation boards according to claim 1, characterized in that, The specific operations of the gradient temperature control module in controlling the pre-sintering process include: The starting temperature reference for the pre-sintering environment is set based on the temperature at which a thermochemical reaction is determined to be non-existent. Starting from the initial temperature reference, a stepped heating action is performed alternately according to the preset temperature increase range and the fixed heat preservation time; During the execution of the stepped heating action, real-time monitoring data fed back by the data acquisition module is received synchronously; after a significant initial curve shift indicating an internal reaction of the material is detected in the feedback data, the current heating rate is maintained, the heat preservation step in the stepped heating action is skipped, until the shift process ends and the temperature returns to the normal physical heating baseline state, and the stepped heating action is resumed. The pre-sintering test is terminated after the last data shift state characterizing the densification shrinkage process is detected, by repeating the response curve shift to switch the heating mode.

3. The automatic loading and unloading energy-saving production system for foamed ceramic insulation boards according to claim 1, characterized in that, The data acquisition module is configured to continuously acquire multi-dimensional sensor data throughout the system's pre-sintering test and actual production cycle. Specific acquisition operations include: The optical volume change data of the green body during the heating process are collected by a laser profile sensor installed at the high-temperature observation window of the main kiln. The actual ambient temperature of the kiln and the actual temperature of the green body are collected by thermocouples arranged on the inner wall of the main kiln and infrared radiation thermometers that are non-contact and aligned with the surface of the green body. The actual preheating temperature of the upper preheating zone and the actual cooling temperature of the lower cooling zone are collected by a sensor network deployed in the double-layer convection heat exchange chamber.

4. The automatic loading and unloading energy-saving production system for foamed ceramic insulation boards according to claim 3, characterized in that, The specific calculation process of the thermodynamic parameter calculation module includes: By combining the optical volume change data of the green blank with the actual temperature of the green blank, the starting point of the last data offset, which represents the continuous shrinkage of the volume, is identified after the green blank undergoes an initial expansion offset under heat and returns to a stable state. The actual temperature of the green blank corresponding to the starting point of the last data offset is extracted as the shrinkage initiation temperature of the material. Calculate the dynamic temperature difference between the actual ambient temperature of the kiln and the actual temperature of the green body, generate the original heat absorption curve reflecting the entire heating process, and smooth the original heat absorption curve to obtain a smooth heat absorption curve. The segment corresponding to the last data shift process in the smooth thermal absorption curve is extracted as the densification characteristic curve. The first derivative of the densification characteristic curve is calculated to find the extreme point of the theoretical optimal heat absorption temperature characterizing the material during the densification process, and the temperature corresponding to the extreme point is taken as the theoretical optimal heat absorption temperature. Perform second derivative calculation on the densification characteristic curve, and extract two adjacent inflection points where the second derivative value is equal to zero, as the heat absorption start boundary and heat absorption end boundary of the densification shrinkage stage. Within the interval formed by the heat absorption initiation boundary and the heat absorption termination boundary, an integral operation is performed on the densification characteristic curve to calculate the cumulative heat absorbed during the densification process, which is taken as the total energy consumption of the material reaction.

5. The automatic loading and unloading energy-saving production system for foamed ceramic insulation boards according to claim 4, characterized in that, The specific process of the calcination simulation module performing multidimensional variable calcination simulation based on the thermodynamic parameters includes: Construct a virtual thermal field environment that includes the physical boundaries of the main kiln and the spatial distribution characteristics of the green body stacking; The number of single-batch loading pieces is used as the spatial arrangement density variable, the calcination temperature is used as the external heat source input variable, and the shrinkage initiation temperature, the theoretical optimal heat absorption temperature, and the total energy consumption of the reaction are used as the target constraints of the material densification reaction and input into the virtual thermal field environment. Based on the spatial arrangement density variable, the kiln airflow obstruction effect and overall thermal inertia that increase with the number of green pieces are dynamically calculated, and the heat attenuation and time lag when external heat is conducted from the outer region of the batch to the geometric center region are deduced, so as to simulate and generate the actual temperature gradient curve of green pieces in different spatial positions within the same batch. in, This represents the effective heat transfer attenuation coefficient caused by spatial arrangement density; Indicates the number of wafers loaded in the current single batch; This indicates the maximum number of kiln cars that can be fully loaded within the physical space of the kiln car; The morphological drag coefficient representing the stacking of green bodies; The interference coefficient represents the penetration of hot air; This represents the cumulative heat actually absorbed by the green body in the geometric center region; This represents the preset system heat transfer coefficient; Indicates the quality of the green body; and These represent the time of the simulation. The kiln ambient temperature and the actual temperature of the central green body at that time; By combining the actual heating gradient curve derived from the theory with the optimal heat absorption temperature, the cumulative time required for the green blanks at each spatial location within the batch to complete the total energy consumption of the reaction is calculated; the amount of heat absorbed by the green blanks in the outer high-temperature region during the heat conduction waiting period is recorded simultaneously to determine the boundary overheating situation. After removing invalid variable combinations where the green body in the central region failed to reach the total energy consumption of the reaction and the green body in the outer region broke through the critical boundary of over-firing, the total time and total heat input consumed by the effective variable combinations in completing the densification reaction of the entire batch are extracted and used as the inferred time and inferred total energy consumption corresponding to each dynamic independent variable combination. The effective variable combinations are then correlated with the corresponding inferred time and inferred total energy consumption to construct a calcination inference mapping dataset.

6. The automatic loading and unloading energy-saving production system for foamed ceramic insulation boards according to claim 5, characterized in that, The specific calculation process of the calcination optimization module includes: Obtain the calcination simulation mapping dataset output by the calcination simulation module, and construct a comprehensive benefit evaluation function that includes production capacity time weight and energy consumption cost weight; in, This represents the comprehensive benefit evaluation value corresponding to the combination of effective variables. This indicates the deduction time corresponding to this combination of variables; This represents the total energy consumption for the deduction corresponding to this combination of variables; and These represent the introduced normalized time reference constant and normalized energy consumption reference constant, respectively, used to eliminate the difference between the time dimension and the heat dimension; This represents the time-weighted coefficient for production capacity. This represents the energy consumption cost weighting coefficient; In the calcination simulation mapping dataset, the simulation time and total simulation energy consumption corresponding to the effective variable combination are respectively used as variables and substituted into the comprehensive benefit evaluation function to calculate the comprehensive benefit evaluation value corresponding to the effective variable combination. Extreme value optimization is performed on all comprehensive benefit evaluation values ​​to screen out the target extreme value point that represents the highest production energy efficiency ratio, and the effective variable combination corresponding to the target extreme value point is extracted; Based on the effective variable combination corresponding to the target extreme point, a preset redundancy amount for absorbing fluctuations in the actual industrial environment is superimposed to generate the theoretical optimal calcination parameters, which include the theoretical optimal calcination temperature, the number of wafers loaded in a single batch, and the processing time of a single batch.

7. The automatic loading and unloading energy-saving production system for foamed ceramic insulation boards according to claim 6, characterized in that, The specific process of the fluid simulation module performing flow field simulation and deduction based on the theoretically optimal calcination parameters includes: The physical model of the double-layer convection heat exchange chamber is established: the structure includes a finished product cooling zone located below, a green preheating zone located above, heat transfer promotion equipment configured in the chamber, and a heat convection channel that naturally rises from the finished product cooling zone to the green preheating zone. Combining the pre-stored indoor capacity extreme value, the number of single-batch loaded pieces is used as the space occupancy benchmark and the single-batch processing time is used as the stepping beat. The total number of physical batches that can be accommodated in the double-layer convection heat exchange chamber is calculated, and the residence time of each batch at a specific cooling position and preheating position is derived. The flow field simulation is constrained in two ways: the finished product cooling zone is constrained to cool down to a safe furnace exit temperature within the residence time. In the high-temperature initial stage near the calcination end of the finished product cooling zone, the cooling rate of the finished product is limited to a preset critical upper limit for preventing thermal cracking. The green preheating zone is constrained to allow the green billet to absorb residual heat from below and reach a predetermined preheating target temperature within the residence time. The flow field is derived based on the constraints of the finished product cooling zone as the primary condition. After the baseline flow field state that meets the requirements of finished product cooling and thermal crack prevention is derived, the actual preheating temperature that the corresponding green billet can obtain is calculated. If the calculated actual preheating temperature does not reach the constraint of the green preheating zone, the simulated operating power of the heat transfer promotion equipment is gradually increased in the simulation model to enhance the heat exchange and transfer efficiency from bottom to top until the temperature states of the upper green and the lower finished product simultaneously meet the bidirectional constraint. Extract the required operating power and matching flow field state of the heat transfer promoting device that simultaneously satisfies the bidirectional constraints, and output them as effective air transport deduction parameters.

8. The automatic loading and unloading energy-saving production system for foamed ceramic insulation boards according to claim 7, characterized in that, The specific calculation and screening process of the fluid optimization module includes: Obtain each set of effective air transport simulation parameters output by the fluid simulation module, and extract the required operating power corresponding to the heat transfer promotion equipment; Based on the determined equipment operating time in the double-layer convection heat exchange chamber, and based on the required operating power and the corresponding equipment operating time, the total energy consumption value of each set of effective air transport simulation parameters in a single operating cycle is obtained by direct summation calculation. All calculated total energy consumption values ​​are compared and optimized to select the optimal combination of deduced parameters with the lowest total energy consumption value as the low-energy-consumption air transmission implementation scheme.

9. The automatic loading and unloading energy-saving production system for foamed ceramic insulation boards according to claim 1, characterized in that, The specific calculation and instruction generation process of the cold state compensation calculation module includes: Define the cold transition time window of the system: take the first batch of green billets stepping into the green billet preheating zone above the double-layer convection heat exchange chamber as the starting node, and take the first batch of calcined high-temperature finished products stepping into the finished product cooling zone below, and take the residual heat released by them reaching the deduction benchmark of the air transmission implementation scheme as the ending node. Within the cold transition time window, the dynamic heat gap at each step is calculated by combining the theoretical heat absorption required for the green billet to reach the predetermined preheating target temperature with the air transmission implementation scheme, due to the complete absence of the bottom and only some high-temperature finished products. Based on the calculated dynamic heat gap, a corresponding initial external heat compensation command is generated. The initial external heat compensation command is configured as follows: at the starting node, the external auxiliary heat source is driven to output peak compensation heat, and within the cold transition time window, as the high-temperature finished products enter the finished product cooling zone in batches, the actual waste heat at the bottom layer rises, and the output power of the external auxiliary heat source is synchronously reduced according to the principle of heat equivalent replacement, until the termination node is reached and the waste heat circulation closed loop is completely formed, at which point the compensation action of the external auxiliary heat source is cut off.

10. The automatic loading and unloading energy-saving production system for foamed ceramic insulation boards according to claim 1, characterized in that, The system also includes an auxiliary execution architecture for performing physical manufacturing and physical closed-loop feedback, specifically including: Multi-temperature zone physical execution module: configured to receive the theoretically optimal calcination parameters, the air transmission implementation scheme and the initial external heat compensation command, drive the heating action of the main kiln, promote the operation of the equipment through heat transfer in the double-layer convection heat exchange chamber, and control the opening and closing of the external auxiliary heat source according to a preset time sequence; Process deviation detection and dynamic evaluation module: After the system enters continuous production, the data acquisition module acquires the actual thermal state of each temperature zone in real time; when comparing the actual thermal state with theoretical parameters, a fault tolerance range that conforms to the logic of actual industrial operation is introduced to filter out normal equipment transient fluctuations; after detecting a substantial deviation beyond the fault tolerance range and a sudden drop in heat data that conforms to the laws of actual industrial physics, the actual heat difference is dynamically calculated and a corrected instantaneous heat compensation command is issued, based on the current physical position and remaining residence time of the batch that deviated in the kiln, to avoid finished product quality defects; Quality mapping and model evolution module: After the physical finished product leaves the kiln and completes physical performance testing, the test results are converted into weighted quality labels; the quality labels are associated with the corresponding batch's operation data and deviation intervention records throughout the entire process and archived to build a bottom-level entity training library; and the data in the entity training library is used to periodically back-calibrate the virtual thermal field environment in the calcination simulation module and fluid simulation module to complete the adaptive closed-loop evolution of the system.

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