Performance optimizing, regulating and controlling method for high-temperature sintering furnace

Abstract

The invention provides a performance optimization and regulation method for a high-temperature sintering furnace, and belongs to the technical field of intelligent regulation, and the performance optimization and regulation method comprises the following steps: arranging sensors in each heating area of the high-temperature sintering furnace, and monitoring the heating areas in real time; constructing a heating area operation state database, comparing the collected real-time data with a preset sintering process parameter range, and analyzing to obtain a performance analysis set of each heating area; establishing a three-dimensional heat conduction model, simulating heat flow distribution of each heating area under different heating powers and temperature settings, determining a thermal coupling effect of each heating area in different stages, and determining a heat transfer coefficient between adjacent heating areas; and an initial strategy of the high-temperature sintering furnace is determined, the initial strategy is optimized based on the auxiliary parameters of all the heating areas, and all the heating areas of the high-temperature sintering furnace are regulated and controlled according to the optimization strategy. The problems of inaccurate temperature control, single parameter analysis, insufficient thermal coupling effect processing and the like in the traditional regulation and control technology are effectively solved.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology, and in particular to a method for performance optimization and control of a high-temperature sintering furnace. Background Technology

[0002] In modern industrial production, high-temperature sintering furnaces, as core equipment for material preparation and processing, are widely used in fields such as electronic ceramics, powder metallurgy, and new energy battery materials. By applying high temperatures to materials, they induce physicochemical reactions between particles, achieving material densification and performance enhancement. With the rapid development of new materials technologies, higher demands are placed on the consistency of sintered product quality, production efficiency, and energy consumption control. Precise control of the heating zone is a key aspect in meeting these requirements. The existing control technologies for high-temperature sintering furnaces have the following shortcomings: First, the temperature control accuracy is insufficient. Due to the complex thermal coupling effect in each heating zone inside the sintering furnace, traditional independent zone temperature control methods are unable to eliminate the temperature gradient between zones, resulting in high product performance dispersion. Second, the monitoring parameters are limited. Most systems rely solely on temperature sensors for feedback control, ignoring the synergistic effects of parameters such as pressure, gas flow rate, and heating element status on the sintering process, and thus failing to comprehensively reflect the operating status of the heating zone. Third, the control strategies lack dynamic adaptability. Existing methods mostly use preset process curves for open-loop control, which is difficult to cope with dynamic factors such as material property fluctuations, environmental changes, and equipment aging, causing actual process parameters to deviate from the optimal range, resulting in increased product defect rates or energy waste. Furthermore, existing technologies have significant shortcomings in multi-source data fusion and in-depth analysis. Although some studies have attempted to describe the heat transfer process using mathematical models, they have not fully integrated real-time monitoring data with historical process data, making it impossible to uncover the potential correlation between heating zone operating parameters and product quality. In terms of control strategy formulation, there is a lack of differentiated treatment for the characteristics of different sintering stages, making it difficult to achieve precise and coordinated control of the heating, holding, and cooling stages.

[0003] Therefore, this invention proposes a method for performance optimization and control of a high-temperature sintering furnace. Summary of the Invention

[0004] This invention provides a method for performance optimization and control of high-temperature sintering furnaces. By using multi-dimensional operating data, in-depth mining of control logic, and adaptation to complex thermal coupling effects, this method aims to break through existing technical bottlenecks and improve the intelligence and precision of industrial sintering processes.

[0005] This invention provides a method for performance optimization and control of a high-temperature sintering furnace, comprising: Step 1: Temperature sensors, pressure sensors, heating elements, and gas flow sensors are installed in each heating zone of the high-temperature sintering furnace to collect temperature data, pressure data, heating power data, and protective gas flow data of each heating zone in real time. Step 2: Construct a database of the operating status of the heating zone, compare the collected real-time data with the preset sintering process parameter range, analyze the temperature fluctuation range, heating power utilization rate and protective gas consumption of each heating zone at the current stage, and obtain the performance analysis set of each heating zone, wherein the performance analysis set contains sub-performance groups of different stages. Step 3: Establish a three-dimensional heat conduction model to simulate the heat flow distribution of each heating zone under different heating power and temperature settings, determine the thermal coupling effect of each heating zone at different stages, and determine the heat transfer coefficient between adjacent heating zones; Step 4: Based on the performance analysis set, establish the mapping relationship between the corresponding heating zone and the control parameters, as well as the heat transfer coefficient, determine the initial strategy of the high-temperature sintering furnace, and optimize the initial strategy based on the auxiliary parameters of each heating zone, so as to control each heating zone of the high-temperature sintering furnace according to the optimized strategy.

[0006] Preferably, the performance analysis set of each heating zone is obtained, including: Determine whether the temperature fluctuation range of the corresponding heating zone exceeds the preset threshold of the corresponding stage; If the fluctuation exceeds the limit, Fourier transform analysis is used to determine the frequency components of the temperature fluctuation and identify the fluctuation factors. If the value is not exceeded, it is determined that there are no fluctuation factors. Determine whether the heating power utilization rate of the corresponding heating zone is lower than the preset utilization rate of the corresponding stage; If it is lower, calculate the actual thermal efficiency by combining the resistance-temperature characteristic curve of the heating element, and compare it with the theoretical thermal efficiency to find out the main reasons for power loss. If it is not lower than, it is determined that there is no primary cause. Determine whether the consumption of protective gas in the corresponding heating zone is outside the consumption range of the corresponding stage; If not, combine the consumption curve of the consumed protective gas to pinpoint the operating difference under the maximum consumption and determine the operating cause of the operating difference; If it exists, it is determined that there is no reason for the operation to occur; Sub-performance groups are formed based on fluctuation factors, main factors, and operational reasons.

[0007] Preferably, the initial strategy is modified based on the auxiliary parameters of each heating zone, including: During the heating stage, the influence of thermal coupling effect on the heating rate of the heating zone is analyzed. When the heating rate of the corresponding heating zone is lower than the first expectation, the additional heating power required is calculated based on the thermal coupling model. During the heat preservation stage, the temperature uniformity of each heating zone is monitored. When the temperature of a corresponding heating zone is lower than the preset temperature, the cause is determined by combining the results of thermal coupling analysis. During the cooling phase, the influence of thermal coupling on the cooling rate is analyzed to determine the first zone that needs to be cooled, and the temperature delay is determined based on the temperature of the adjacent heating zone and the distribution of cooling gas in the first zone. The supplementary results, the causes, and the temperature delay are used as auxiliary parameters for the corresponding stages, and the initial strategy is optimized based on the auxiliary parameters.

[0008] Preferably, determining the initial strategy for the high-temperature sintering furnace includes: Collect a large amount of historical sintering data, including the operating parameters of each heating zone and the quality data of sintered products under different sintering materials and different sintering processes, and construct a training dataset; A convolutional neural network is used to train the training dataset to establish a mapping model between the operating parameters of the heating zone and the quality of the sintered product. Based on the mapping model, it is identified in real time whether each heating zone is in the optimal sintering mode at the current stage. When a deviation from the optimal mode is detected, an adjustment command is automatically generated; Simultaneously, based on the mapping relationship between each analysis parameter in the performance analysis set and the corresponding heating zone's control parameters at the current stage, adjustment sub-information for each analysis parameter is obtained; All adjustment sub-information is combined to obtain a first strategy for the corresponding heating zone, and the first strategy is fused based on the control command to obtain a separate strategy; The initial strategy of the high-temperature sintering furnace is determined by combining the individual strategies of each heating zone with the heat transfer coefficient.

[0009] Preferably, after obtaining the optimization strategy, the following steps are also included: When the optimization strategy is related to the heating element, the remaining lifespan of the heating element is calculated based on the lifespan prediction model of the heating element. When the remaining lifespan is lower than the preset lifespan, the heating power distribution of the corresponding heating zone is automatically adjusted, and a maintenance warning is issued to prompt staff to replace or repair the heating element.

[0010] Preferably, the life prediction model for the heating element is established by installing temperature strain sensors and resistance monitoring modules on the heating elements in each heating zone, and collecting data on the temperature distribution, mechanical strain, and resistance changes of the heating elements in real time.

[0011] Preferably, after adjusting the heating zones of the high-temperature sintering furnace according to the optimization strategy, the process further includes: Continue to monitor the adjusted heating zone. If it still does not meet the standards, analyze the first impact of environmental temperature change on the heat dissipation efficiency of the heating zone, the second impact of humidity change on the insulation performance of the insulation layer, the third impact of air pressure change on the flow characteristics of the protective gas, and the fourth impact of vibration on the connection reliability of the sensor and heating element based on the correlation model of environmental factors and heating zone operating parameters. Based on the first, second, third, and fourth effects, the optimization strategy is further modified for regulation.

[0012] Preferably, the environmental factor-heating zone operating parameter correlation model is established by setting temperature and humidity sensors, air pressure sensors and vibration sensors in the external environment of the high-temperature sintering furnace to collect ambient temperature, humidity, atmospheric pressure and equipment vibration data in real time.

[0013] Preferably, the initial strategy of the high-temperature sintering furnace is determined by performing fusion processing according to the individual strategies of each heating zone and combining the heat transfer coefficient, including: Constructing the heat transfer coupling matrix of the heating zone ,in, This represents the heat transfer coefficient between the i-th heating zone and the j-th heating zone; Define the control parameter vector corresponding to the individual strategy for each heating zone. , This represents the p-th control parameter in the i-th heating zone; Establish a state-space model for the fusion strategy:

[0014] in, This represents the temperature vector for each heating zone; The influence matrix of the control parameters; External interference matrix; This is the environmental disturbance vector; This is the vector of control parameters for all heating zones; Define the policy fusion objective function J: ; in, This is the temperature fluctuation vector; This is a preset temperature curve vector; , , These are the weighting coefficients; The objective function is solved using a convex optimization algorithm to obtain the globally optimal control parameter vector that satisfies the heat transfer coupling constraint. This forms the initial strategy for the high-temperature sintering furnace.

[0015] Preferably, the fluctuation factors are related to heating element failure, airflow disturbance, and uneven heat conduction, and the main causes are related to heating element aging and insulation layer damage.

[0016] Compared with the prior art, the beneficial effects of this application are as follows: Through multi-dimensional data collection, in-depth analysis, and precise modeling, comprehensive monitoring and quantitative evaluation of the operating status of each heating zone in the high-temperature sintering furnace were achieved, effectively solving problems such as inaccurate temperature control, limited parameter analysis, and insufficient handling of thermal coupling effects in traditional control technologies. The optimized control strategy based on performance analysis and the thermal coupling model can significantly improve the quality consistency of sintered products and reduce the product defect rate. By rationally adjusting the heating power and protective gas flow rate, energy consumption can be reduced and production efficiency improved. Simultaneously, dynamically adapting to environmental changes and material differences enhances the stability and reliability of the high-temperature sintering furnace operation.

[0017] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0018] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0019] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart of a method for performance optimization and control of a high-temperature sintering furnace according to an embodiment of the present invention. Detailed Implementation

[0020] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0021] This invention provides a method for performance optimization and control of a high-temperature sintering furnace, such as... Figure 1 As shown, it includes: Step 1: Temperature sensors, pressure sensors, heating elements, and gas flow sensors are installed in each heating zone of the high-temperature sintering furnace to collect temperature data, pressure data, heating power data, and protective gas flow data of each heating zone in real time. Step 2: Construct a database of the operating status of the heating zone, compare the collected real-time data with the preset sintering process parameter range, analyze the temperature fluctuation range, heating power utilization rate and protective gas consumption of each heating zone at the current stage, and obtain the performance analysis set of each heating zone, wherein the performance analysis set contains sub-performance groups of different stages. Step 3: Establish a three-dimensional heat conduction model to simulate the heat flow distribution of each heating zone under different heating power and temperature settings, determine the thermal coupling effect of each heating zone at different stages, and determine the heat transfer coefficient between adjacent heating zones; Step 4: Based on the performance analysis set, establish the mapping relationship between the corresponding heating zone and the control parameters, as well as the heat transfer coefficient, determine the initial strategy of the high-temperature sintering furnace, and optimize the initial strategy based on the auxiliary parameters of each heating zone, so as to control each heating zone of the high-temperature sintering furnace according to the optimized strategy.

[0022] In this embodiment, the heating zone is an independent heating area inside the high-temperature sintering furnace, divided according to process requirements. Different temperature curves can be set for different heating zones to meet the sintering requirements of materials at different stages.

[0023] In this embodiment, in the high-temperature sintering furnace, type B thermocouples are commonly used to measure temperatures above 1600°C and provide real-time feedback on the temperature of each heating zone. The pressure sensor is a diffused silicon pressure sensor, which can accurately measure the pressure change of 0-1 MPa inside the furnace to ensure that the sintering process is carried out under a suitable pressure environment. The heating element is a component that provides heat to the sintering furnace, and common examples include resistance wires and silicon molybdenum rods. A thermal gas mass flow meter is used to accurately measure the flow rate of protective gases (such as argon and nitrogen) to ensure the gas protection effect during the sintering process.

[0024] The heating zone operation status database is a database system used to store real-time operation data and historical data of each heating zone of the high-temperature sintering furnace. It can use relational databases such as MySQL to record the changes in temperature, pressure, power and other data of each heating zone over time. The sintering process parameter range is a pre-set allowable range of process parameters based on different sintering materials and product requirements. For example, in ceramic sintering, the heating rate is set to 5-10℃ / min, and the holding temperature is set to 1200-1300℃. Temperature fluctuation range is the range of deviation between the actual temperature of the heating zone and the set temperature at a certain moment. For example, if the set temperature of a heating zone is 1000℃ and the actual temperature fluctuates between 995-1005℃, then the temperature fluctuation range is ±5℃. The heating power utilization rate is the ratio of the effective power actually used for heating materials to the total input power. For example, if the input power is 100kW and the effective heating power is calculated to be 80kW through heat balance, then the heating power utilization rate is 80%. Protective gas consumption refers to the total amount of protective gas consumed during the sintering process, such as 50 cubic meters of nitrogen being consumed in a single sintering process. The performance analysis set is a collection of results formed after comprehensive analysis of the operating status of each heating zone. It includes sub-performance groups for different sintering stages (heating, holding, and cooling). For example, the sub-performance group for the heating stage includes indicators such as the heating rate compliance rate and temperature overshoot. The three-dimensional heat conduction model is a mathematical model based on the principle of heat transfer that describes the three-dimensional heat transfer process in a high-temperature sintering furnace. It can be constructed using finite element analysis software (such as ANSYS), which divides the sintering furnace into multiple tiny units to simulate the conduction, convection and radiation of heat flow between the units. Heat flow distribution refers to the path and intensity distribution of heat transfer within a high-temperature sintering furnace. It is calculated using a three-dimensional heat conduction model. For example, simulation results show that the heat flow density is higher near the furnace wall and relatively lower in the central region. Thermal coupling effect is a phenomenon in which different heating zones in a high-temperature sintering furnace influence each other through heat conduction, convection and radiation. For example, an increase in the temperature of one heating zone can cause a change in the temperature of adjacent heating zones. The heat transfer coefficient represents the amount of heat transferred through a unit area per unit time under a unit temperature difference. It is used to quantify the strength of thermal coupling between different heating zones, and its unit is 1 / 2 oz. . Control parameters are parameters used to regulate the operating status of high-temperature sintering furnaces, including the power supply voltage of heating elements, the flow rate of protective gas, and the start and stop of auxiliary heating devices. The mapping relationship is the correspondence between the performance indicators of the heating zone and the control parameters established through data analysis and modeling. For example, it establishes a functional relationship between the temperature fluctuation amplitude and the adjustment amount of the power supply voltage of the heating element. The initial strategy is a high-temperature sintering furnace control strategy initially formulated based on the performance analysis set and heat transfer coefficient, such as setting the initial heating power curve of each heating zone during the heating stage. Auxiliary parameters are other parameters that affect the control strategy besides the main performance indicators, such as ambient temperature and batch differences of materials. For example, when the ambient temperature is high, the power of the cooling system needs to be increased. The optimization strategy is the final control strategy obtained by adjusting and optimizing the initial strategy after taking into account auxiliary parameters. The beneficial effects of the above technical solution are as follows: Through multi-dimensional data collection, in-depth analysis, and precise modeling, comprehensive monitoring and quantitative evaluation of the operating status of each heating zone in the high-temperature sintering furnace are achieved, effectively solving problems such as inaccurate temperature control, single parameter analysis, and insufficient handling of thermal coupling effects in traditional control technologies. The optimized control strategy based on performance analysis and thermal coupling models can significantly improve the quality consistency of sintered products and reduce the product defect rate; by rationally adjusting the heating power and protective gas flow rate, energy consumption can be reduced and production efficiency improved; simultaneously, dynamically adapting to environmental changes and material differences enhances the stability and reliability of the high-temperature sintering furnace operation.

[0025] This invention provides a method for performance optimization and control of a high-temperature sintering furnace, obtaining a performance analysis set for each heating zone, including: Determine whether the temperature fluctuation range of the corresponding heating zone exceeds the preset threshold of the corresponding stage; If the fluctuation exceeds the limit, Fourier transform analysis is used to determine the frequency components of the temperature fluctuation and identify the fluctuation factors. If the value is not exceeded, it is determined that there are no fluctuation factors. Determine whether the heating power utilization rate of the corresponding heating zone is lower than the preset utilization rate of the corresponding stage; If it is lower, calculate the actual thermal efficiency by combining the resistance-temperature characteristic curve of the heating element, and compare it with the theoretical thermal efficiency to find out the main reasons for power loss. If it is not lower than, it is determined that there is no primary cause. Determine whether the consumption of protective gas in the corresponding heating zone is outside the consumption range of the corresponding stage; If not, combine the consumption curve of the consumed protective gas to pinpoint the operating difference under the maximum consumption and determine the operating cause of the operating difference; If it exists, it is determined that there is no reason for the operation to occur; Sub-performance groups are formed based on fluctuation factors, main factors, and operational reasons.

[0026] Preferably, the fluctuation factors are related to heating element failure, airflow disturbance, and uneven heat conduction, and the main causes are related to heating element aging and insulation layer damage.

[0027] In this embodiment, the preset threshold for the corresponding stage is the allowable temperature fluctuation range set for each sintering stage (heating, holding, and cooling) according to the sintering process requirements. For example, in the heating stage of graphitization sintering of lithium battery anode materials, the preset temperature fluctuation threshold may be ±3℃ to ensure the uniform formation of the material's crystal structure. In this embodiment, the frequency components of the temperature fluctuation are the energy distribution of the temperature fluctuation signal at different frequencies after Fourier transform. For example, if the analysis finds high-frequency components (such as 10Hz) in the temperature fluctuation signal, it may indicate the presence of rapid airflow disturbances; low-frequency components (such as 0.1Hz) may be related to uneven heat conduction.

[0028] Fluctuation factors are the main causes of excessive temperature fluctuations in the heating zone. These include heating element malfunctions (such as partial breakage of the resistance wire), airflow disturbances (such as unstable protective gas flow rate), and uneven heat conduction (such as excessively rapid heat dissipation in certain areas of the furnace wall). For example, if the Fourier transform shows that the temperature fluctuations have a specific frequency of periodic changes, combined with abnormal heating element operating current, it can be determined that the problem is caused by a heating element malfunction.

[0029] In this embodiment, the heating power utilization rate is the percentage of the power actually used to heat the material and generate effective heat, relative to the total input power. The calculation formula is: Heating power utilization rate = (Effective heating power / Total input power) × 100%. For example, if the input heating power is 200kW, and the effective heating power is calculated to be 160kW based on heat balance, then the heating power utilization rate is 80%.

[0030] The preset utilization rate for each stage is a heating power utilization efficiency standard set for each sintering stage based on the sintering process and equipment parameters. In the heat preservation stage of cemented carbide sintering, the preset heating power utilization rate may need to reach over 90% to ensure efficient energy use. In this embodiment, the resistance-temperature characteristic curve of the heating element describes the relationship between the resistance value of the heating element and the temperature. Heating elements made of different materials (such as silicon molybdenum rods and molybdenum wires) have different resistance-temperature characteristics. For example, silicon molybdenum rods have low resistance at room temperature, and the resistance gradually increases with increasing temperature, exhibiting a non-linear relationship. Actual thermal efficiency is the ratio of the energy actually used in effective thermal processes such as material heating and phase change to the input electrical energy. By measuring the material's temperature change, mass, and specific heat capacity, combined with the heating time, the actual heat absorbed can be calculated, and thus the actual thermal efficiency can be obtained. Theoretical thermal efficiency is the heating efficiency calculated based on the law of conservation of energy under ideal conditions (no heat loss and no loss of heating element). For example, assuming an input of 100 kJ of electrical energy, if the material should theoretically absorb 95 kJ of heat, then the theoretical thermal efficiency is 95%. Power loss is the main cause of low heating power utilization. Common causes include aging of heating elements (performance degradation, abnormal resistance) and damage to the insulation layer (significant heat loss). If the actual thermal efficiency is much lower than the theoretical thermal efficiency, and the resistance value of the heating element deviates from its normal resistance-temperature characteristic curve, it can be determined that it is caused by aging of the heating element. Protective gas consumption refers to the total volume or mass of protective gases (such as argon and nitrogen) consumed in a high-temperature sintering furnace during a specific sintering stage. For example, in the sintering process of magnetic materials, the consumption of argon protective gas in one sintering cycle is 80 cubic meters. The consumption range for each stage is a reasonable range for protective gas consumption set according to the sintering process requirements and equipment parameters. During the cooling stage of metal powder sintering, the protective gas consumption may be set at 50-70 cubic meters. The consumption curve of the protective gas reflects the change in the amount of protective gas consumed over time, and can intuitively show the rate and trend of gas consumption. Under normal circumstances, the consumption curve should conform to the preset process curve pattern. The operational variance at maximum consumption is the deviation between actual operating parameters (such as flow rate and pressure) and preset parameters when the protective gas consumption reaches its peak. For example, the preset maximum flow rate is... In fact, The difference is . Reasons for abnormal operation: Factors causing abnormal protective gas consumption may include gas pipeline leaks, flow control valve malfunctions, and improper process parameter settings. For example, if the consumption curve shows an abnormally sharp increase and the gas pressure drops suddenly, it can be determined that there is a gas pipeline leak. Sub-performance groups are collections of performance analyses for a specific sintering stage or heating zone, formed by integrating key information obtained from the above analysis, such as temperature fluctuation factors, main causes of power loss, and reasons for protective gas consumption. For example, the sub-performance group for the heating stage in a certain heating zone includes information such as "temperature fluctuation factors: airflow disturbance," "main causes of power loss: insulation layer damage," and "operational reasons: gas pipeline leakage." The beneficial effects of the above technical solution are: through in-depth analysis of key operating parameters in the heating zone of the high-temperature sintering furnace, accurate diagnosis of abnormal equipment conditions is achieved. Specifically, it can quickly locate the root causes of abnormal temperature fluctuations, power losses, and gas consumption, avoiding product quality defects (such as overheating of materials or uneven density) caused by abnormalities in a single parameter.

[0031] This invention provides a method for performance optimization and control of a high-temperature sintering furnace, which modifies the initial strategy based on auxiliary parameters of each heating zone, including: During the heating stage, the influence of thermal coupling effect on the heating rate of the heating zone is analyzed. When the heating rate of the corresponding heating zone is lower than the first expectation, the additional heating power required is calculated based on the thermal coupling model. During the heat preservation stage, the temperature uniformity of each heating zone is monitored. When the temperature of a corresponding heating zone is lower than the preset temperature, the cause is determined by combining the results of thermal coupling analysis. During the cooling phase, the influence of thermal coupling on the cooling rate is analyzed to determine the first zone that needs to be cooled, and the temperature delay is determined based on the temperature of the adjacent heating zone and the distribution of cooling gas in the first zone. The supplementary results, the causes, and the temperature delay are used as auxiliary parameters for the corresponding stages, and the initial strategy is optimized based on the auxiliary parameters.

[0032] In this embodiment, the thermal coupling effect is a phenomenon in which different heating zones within a high-temperature sintering furnace influence each other through heat conduction, convection, and radiation. For example, adjacent high-temperature heating zones can passively raise the temperature of low-temperature heating zones through thermal radiation, interfering with their heating rate. The heating rate is the rate by which the temperature of the heating zone increases per unit time, and its unit is usually 1. For example, during the sintering of lithium battery cathode materials, the heating stage requires... The rate of temperature increase is from room temperature to 800°C. The first expectation is based on the ideal heating rate target value pre-set in the sintering process. For example, a certain special ceramic sintering process requires the heating rate to be stable at 8 for the first 30 minutes of the heating stage. This value is the first expectation. The additional heating power is the electrical power that needs to be applied to the heating zone to bring the temperature to the target heating curve when the actual heating rate is lower than the first expected rate. The unit is kW. Temperature uniformity refers to the degree of temperature consistency within and between different heating zones during the holding stage, and is usually measured by the maximum temperature difference. For example, the sintering of aerospace components requires that the temperature difference within the furnace during the holding stage not exceed ±5°C. . The preset temperature is a target temperature value for the holding stage, set according to the characteristics of the sintered material. For example, the holding temperature for sintering cemented carbide cutting tools is 1400°C. This promotes uniform grain growth. The root cause of the heating zone temperature being lower than the preset temperature may include heat loss due to thermal coupling, localized failure of heating elements, and damage to the insulation layer. For example, during the heat preservation stage of magnesium alloy powder sintering, the temperature of the third heating zone remained below the preset 650℃. Thermal coupling analysis revealed that this was due to the upward flow of air from the lower cooling zone carrying away heat. By adding a heat insulation baffle at the bottom of this zone and providing compensatory heating to adjacent heating zones, the temperature uniformity was restored to the process requirements.

[0033] In this embodiment, the cooling rate is the rate at which the temperature of the heating zone decreases per unit time, and the unit is _____. For example, after the separator of a new energy battery is sintered, it is required to have a strength of 10. The rate at which it decreases to room temperature.

[0034] The first zone is the target heating zone that needs to be cooled first during the cooling stage. It is usually a temperature-sensitive area or a region that is prone to internal stress.

[0035] Temperature delay is a phenomenon where the actual cooling time of the first zone lags behind the theoretical cooling time due to thermal coupling. For example, theoretically, a certain zone should cool to the target temperature within 10 minutes, but due to heat conduction from adjacent high-temperature zones, it actually takes 15 minutes, resulting in a temperature delay of 5 minutes. For instance, when cooling ceramic matrix composites, the central heating zone (first zone) needs rapid cooling to avoid grain coarsening, but the cooling rate is insufficient due to thermal coupling from the surrounding high-temperature zones. By adjusting the cooling gas inlet angle through CFD simulation and simultaneously implementing thermal insulation for adjacent areas, the temperature delay was shortened from 8 minutes to 3 minutes, ensuring the material's mechanical properties.

[0036] Supplementary result: The additional heating power calculated during the heating phase.

[0037] Cause: The root cause of the temperature anomaly was identified during the insulation stage analysis.

[0038] Temperature delay: A quantified cooling time lag parameter during the cooling phase.

[0039] The beneficial effects of the above technical solution are: it solves the problems of rate runaway, uneven temperature, and cooling delay in the heating, heat preservation, and cooling stages respectively, dynamically optimizes heating power and gas flow, locates potential equipment faults through thermal coupling analysis, and transforms passive maintenance into proactive maintenance.

[0040] This invention provides a method for performance optimization and control of a high-temperature sintering furnace, comprising determining an initial strategy for the high-temperature sintering furnace, including: Collect a large amount of historical sintering data, including the operating parameters of each heating zone and the quality data of sintered products under different sintering materials and different sintering processes, and construct a training dataset; A convolutional neural network is used to train the training dataset to establish a mapping model between the operating parameters of the heating zone and the quality of the sintered product. Based on the mapping model, it is identified in real time whether each heating zone is in the optimal sintering mode at the current stage. When a deviation from the optimal mode is detected, an adjustment command is automatically generated; Simultaneously, based on the mapping relationship between each analysis parameter in the performance analysis set and the corresponding heating zone's control parameters at the current stage, adjustment sub-information for each analysis parameter is obtained; All adjustment sub-information is combined to obtain a first strategy for the corresponding heating zone, and the first strategy is fused based on the control command to obtain a separate strategy; The initial strategy of the high-temperature sintering furnace is determined by combining the individual strategies of each heating zone with the heat transfer coefficient.

[0041] Preferably, the initial strategy of the high-temperature sintering furnace is determined by performing fusion processing according to the individual strategies of each heating zone and combining the heat transfer coefficient, including: Constructing the heat transfer coupling matrix of the heating zone ,in, This represents the heat transfer coefficient between the i-th heating zone and the j-th heating zone; Define the control parameter vector corresponding to the individual strategy for each heating zone. , This represents the p-th control parameter in the i-th heating zone; Establish a state-space model for the fusion strategy:

[0042] in, This represents the temperature vector for each heating zone; The influence matrix of the control parameters; External interference matrix; This is the environmental disturbance vector; This is the vector of control parameters for all heating zones; Define the policy fusion objective function J: ; in, This is the temperature fluctuation vector; This is a preset temperature curve vector; , , These are the weighting coefficients; The objective function is solved using a convex optimization algorithm to obtain the globally optimal control parameter vector that satisfies the heat transfer coupling constraint. This forms the initial strategy for the high-temperature sintering furnace.

[0043] In this embodiment, historical sintering data refers to various types of data generated during past high-temperature sintering processes, covering equipment operating status, process parameter settings, and product quality test results, which forms the basis for analyzing sintering patterns. Sintering materials are raw materials used for high-temperature sintering, such as lithium iron phosphate, a cathode material for lithium batteries, metal powders (stainless steel powder, tungsten powder), and ceramic raw materials (alumina, zirconium oxide). The sintering characteristics of different materials vary significantly. The sintering process is a combination of parameters such as temperature profile, heating rate, holding time, type and flow rate of protective gas, which are tailored for specific sintering materials. For example, the sintering of cemented carbide tools requires high temperature and high pressure and long holding time. Operating parameters are real-time data of each heating zone of the high-temperature sintering furnace during operation, including temperature, pressure, heating power, gas flow rate, and heating element resistance. Sintered product quality data are indicators that reflect the performance of the product after sintering, such as the conductivity of lithium battery electrode materials, the density and hardness of metal products, and the compressive strength and porosity of ceramic components. The training dataset is a collection of historical sintering data that has been filtered, cleaned, and labeled for use in training machine learning models. It is the core material for establishing mapping relationships. In this embodiment, the mapping model is a mathematical model based on neural network training that describes the quantitative relationship between the operating parameters of the heating zone and the quality of sintered products. It can be used to predict the product quality under different parameter combinations. The optimal sintering mode is the combination of heating zone operating parameters that achieves the best sintered product quality, the highest production efficiency, and the lowest energy consumption. Different materials and processes correspond to different optimal modes.

[0044] Control commands are automatically generated by the system when it detects a deviation from the optimal sintering mode. These commands are used to adjust the operating status of the high-temperature sintering furnace, such as adjusting the heating power, changing the gas flow rate, and starting or stopping auxiliary equipment. In this embodiment, the control parameters are parameters used to adjust the operating status of the high-temperature sintering furnace, such as the voltage of the heating element and the opening degree of the gas flow control valve. The adjustment sub-information is based on the mapping relationship between the analysis parameters and the control parameters in the performance analysis set. It provides specific control suggestions for each analysis parameter, such as "when the temperature fluctuation exceeds the limit, reduce the heating element voltage by 5%". In this embodiment, the first strategy is to initially combine the adjustment sub-information of each analysis parameter to form a draft control strategy for a single heating zone. The individual strategy is to combine the first strategy with automatically generated control instructions for fusion and optimization to obtain the final control strategy applicable to a single heating zone. The state-space model is a mathematical model used to describe the dynamic behavior of a system. In this scheme, it is used to characterize the relationship between temperature changes in the heating zone and control parameters and external disturbances. The strategy fusion objective function is constructed with the objectives of minimizing temperature fluctuations, minimizing the cost of control parameters, and minimizing temperature tracking errors. The globally optimal control parameters are determined by optimizing this function. The initial strategy is an overall control strategy for the high-temperature sintering furnace determined by combining the individual strategies of each heating zone and considering the heat transfer coupling effect. For example, in a multi-zone linked high-temperature sintering furnace, a 3×3 heat transfer coupling matrix is ​​constructed to describe the heat transfer relationship between the three heating zones. The objective function is solved using a convex optimization algorithm to obtain the optimal control parameters for each heating zone, such as increasing the heating power of the first heating zone by 12% and reducing the gas flow rate of the second heating zone by 8%, which are then combined to form the initial strategy. The beneficial effects of the above technical solution are as follows: by combining data-driven and mathematical modeling, the intelligent generation of control strategies for high-temperature sintering furnaces is realized. Specifically, the model trained based on historical data can accurately predict product quality under different operating parameters, identify in advance the state of deviation from the optimal mode, and realize the coordinated control of each heating zone by considering the heat transfer coupling effect and multi-objective optimization of the initial strategy. By updating the training dataset, the model and strategy can quickly adapt to the needs of new product development and process improvement.

[0045] This invention provides a method for performance optimization and control of a high-temperature sintering furnace, which, after obtaining the optimization strategy, further includes: When the optimization strategy is related to the heating element, the remaining lifespan of the heating element is calculated based on the lifespan prediction model of the heating element. When the remaining lifespan is lower than the preset lifespan, the heating power distribution of the corresponding heating zone is automatically adjusted, and a maintenance warning is issued to prompt staff to replace or repair the heating element.

[0046] Preferably, the life prediction model for the heating element is established by installing temperature strain sensors and resistance monitoring modules on the heating elements in each heating zone, and collecting data on the temperature distribution, mechanical strain, and resistance changes of the heating elements in real time.

[0047] The beneficial effect of the above technical solution is that by determining the lifespan of the heating element and avoiding abnormalities of the heating element, the temperature control efficiency of the heating zone can be guaranteed.

[0048] This invention provides a method for performance optimization and control of a high-temperature sintering furnace. After controlling each heating zone of the high-temperature sintering furnace according to the optimization strategy, the method further includes: Continue to monitor the adjusted heating zone. If it still does not meet the standards, analyze the first impact of environmental temperature change on the heat dissipation efficiency of the heating zone, the second impact of humidity change on the insulation performance of the insulation layer, the third impact of air pressure change on the flow characteristics of the protective gas, and the fourth impact of vibration on the connection reliability of the sensor and heating element based on the correlation model of environmental factors and heating zone operating parameters. Based on the first, second, third, and fourth effects, the optimization strategy is further modified for regulation.

[0049] Preferably, the environmental factor-heating zone operating parameter correlation model is established by setting temperature and humidity sensors, air pressure sensors and vibration sensors in the external environment of the high-temperature sintering furnace to collect ambient temperature, humidity, atmospheric pressure and equipment vibration data in real time.

[0050] In this embodiment, the adjusted heating zone refers to each heating zone of the high-temperature sintering furnace after the operating parameters are adjusted by executing the optimization strategy, such as a specific heating zone after adjusting the heating power and gas flow rate.

[0051] Meeting the standards means that the operating parameters of the heating zone and the quality of the sintered product meet the preset process standards. For example, during the sintering of lithium battery cathode materials, the temperature of the heating zone is stable within the set value ±3℃, and the product conductivity meets the standards. Environmental Factors-Heating Zone Operating Parameter Correlation Model: A mathematical model is established by analyzing the relationship between environmental data (temperature, humidity, air pressure, vibration) and heating zone operating parameters to predict the impact of environmental changes on the sintering process. The first impact: The effect of ambient temperature changes on the heat dissipation efficiency of the heating zone. When the temperature rises, the temperature difference between the furnace body and the outside environment decreases, heat dissipation slows down, and the actual temperature of the heating zone may be higher than the set value. The second impact: the effect of humidity changes on the insulation performance of the insulation layer. In high humidity environments, the thermal conductivity of the insulation layer increases after absorbing water, heat loss accelerates, and it becomes difficult for the heating zone to heat up. The third impact: The effect of air pressure changes on the flow characteristics of protective gas. When the air pressure decreases, the gas flow rate may be insufficient, failing to effectively isolate the material from air and leading to oxidation. Fourth impact: The effect of vibration on the reliability of the connection between the sensor and the heating element. Continuous vibration may cause the temperature sensor to shift, distort the collected data, and affect the accuracy of the control. In this embodiment, the optimization strategy is a high-temperature sintering furnace control scheme formulated based on previous performance analysis and thermal coupling effect, including parameter adjustment strategies such as heating power and gas flow rate. The revision involves adjusting and improving the optimization strategy based on the results of the environmental impact analysis.

[0052] Re-adjustment involves applying the revised optimization strategy to the high-temperature sintering furnace and readjusting the operating parameters of the heating zone. The beneficial effects of the above technical solution are: by incorporating environmental factors into the high-temperature sintering furnace control system, the stability of the sintering process and product quality are significantly improved. Specifically, the impact of environmental changes on the heating zone is analyzed in real time, so that the sintering process is no longer constrained by external conditions. By monitoring the impact of vibration and humidity on the equipment, sensor failures and heating element damage can be prevented in advance, and the control strategy can be accurately corrected to avoid energy waste caused by environmental factors.

[0053] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for performance optimization and control of a high-temperature sintering furnace, characterized in that, include: Step 1: Temperature sensors, pressure sensors, heating elements, and gas flow sensors are installed in each heating zone of the high-temperature sintering furnace to collect temperature data, pressure data, heating power data, and protective gas flow data of each heating zone in real time. Step 2: Construct a database of the operating status of the heating zone, compare the collected real-time data with the preset sintering process parameter range, analyze the temperature fluctuation range, heating power utilization rate and protective gas consumption of each heating zone at the current stage, and obtain the performance analysis set of each heating zone, wherein the performance analysis set contains sub-performance groups of different stages. Step 3: Establish a three-dimensional heat conduction model to simulate the heat flow distribution of each heating zone under different heating power and temperature settings, determine the thermal coupling effect of each heating zone at different stages, and determine the heat transfer coefficient between adjacent heating zones; Step 4: Based on the performance analysis set, establish the mapping relationship between the corresponding heating zone and the control parameters, as well as the heat transfer coefficient, determine the initial strategy of the high-temperature sintering furnace, and optimize the initial strategy based on the auxiliary parameters of each heating zone, so as to control each heating zone of the high-temperature sintering furnace according to the optimized strategy.

2. The method for optimizing and controlling the performance of a high-temperature sintering furnace according to claim 1, characterized in that, The performance analysis set for each heating zone was obtained, including: Determine whether the temperature fluctuation range of the corresponding heating zone exceeds the preset threshold of the corresponding stage; If the fluctuation exceeds the limit, Fourier transform analysis is used to determine the frequency components of the temperature fluctuation and identify the fluctuation factors. If the value is not exceeded, it is determined that there are no fluctuation factors. Determine whether the heating power utilization rate of the corresponding heating zone is lower than the preset utilization rate of the corresponding stage; If it is lower, calculate the actual thermal efficiency by combining the resistance-temperature characteristic curve of the heating element, and compare it with the theoretical thermal efficiency to find out the main reasons for power loss. If it is not lower than, it is determined that there is no primary cause. Determine whether the consumption of protective gas in the corresponding heating zone is outside the consumption range of the corresponding stage; If not, combine the consumption curve of the consumed protective gas to pinpoint the operating difference under the maximum consumption and determine the operating cause of the operating difference; If it exists, it is determined that there is no reason for the operation to occur; Sub-performance groups are formed based on fluctuation factors, main factors, and operational reasons.

3. The method for optimizing and controlling the performance of a high-temperature sintering furnace according to claim 1, characterized in that, The initial strategy is modified based on the auxiliary parameters of each heating zone, including: During the heating stage, the influence of thermal coupling effect on the heating rate of the heating zone is analyzed. When the heating rate of the corresponding heating zone is lower than the first expectation, the additional heating power required is calculated based on the thermal coupling model. During the heat preservation stage, the temperature uniformity of each heating zone is monitored. When the temperature of a corresponding heating zone is lower than the preset temperature, the cause is determined by combining the results of thermal coupling analysis. During the cooling phase, the influence of thermal coupling on the cooling rate is analyzed to determine the first zone that needs to be cooled, and the temperature delay is determined based on the temperature of the adjacent heating zone and the distribution of cooling gas in the first zone. The supplementary results, the causes, and the temperature delay are used as auxiliary parameters for the corresponding stages, and the initial strategy is optimized based on the auxiliary parameters.

4. The method for optimizing and controlling the performance of a high-temperature sintering furnace according to claim 1, characterized in that, Determining the initial strategy for the high-temperature sintering furnace includes: Collect a large amount of historical sintering data, including the operating parameters of each heating zone and the quality data of sintered products under different sintering materials and different sintering processes, and construct a training dataset; A convolutional neural network is used to train the training dataset to establish a mapping model between the operating parameters of the heating zone and the quality of the sintered product. Based on the mapping model, it is identified in real time whether each heating zone is in the optimal sintering mode at the current stage. When a deviation from the optimal mode is detected, an adjustment command is automatically generated; Simultaneously, based on the mapping relationship between each analysis parameter in the performance analysis set and the corresponding heating zone's control parameters at the current stage, adjustment sub-information for each analysis parameter is obtained; All adjustment sub-information is combined to obtain a first strategy for the corresponding heating zone, and the first strategy is fused based on the control command to obtain a separate strategy; The initial strategy of the high-temperature sintering furnace is determined by combining the individual strategies of each heating zone with the heat transfer coefficient.

5. The method for optimizing and controlling the performance of a high-temperature sintering furnace according to claim 1, characterized in that, After obtaining the optimization strategy, it also includes: When the optimization strategy is related to the heating element, the remaining lifespan of the heating element is calculated based on the lifespan prediction model of the heating element. When the remaining lifespan is lower than the preset lifespan, the heating power distribution of the corresponding heating zone is automatically adjusted, and a maintenance warning is issued to prompt staff to replace or repair the heating element.

6. The method for optimizing and controlling the performance of a high-temperature sintering furnace according to claim 5, characterized in that, The life prediction model for the heating element is established by installing temperature strain sensors and resistance monitoring modules on the heating elements in each heating zone, and collecting data on the temperature distribution, mechanical strain, and resistance changes of the heating elements in real time.

7. The method for performance optimization and control of a high-temperature sintering furnace according to claim 1, characterized in that, After adjusting the heating zones of the high-temperature sintering furnace according to the optimization strategy, the following is also included: Continue to monitor the adjusted heating zone. If it still does not meet the standards, analyze the first impact of environmental temperature change on the heat dissipation efficiency of the heating zone, the second impact of humidity change on the insulation performance of the insulation layer, the third impact of air pressure change on the flow characteristics of the protective gas, and the fourth impact of vibration on the connection reliability of the sensor and heating element based on the correlation model of environmental factors and heating zone operating parameters. Based on the first, second, third, and fourth effects, the optimization strategy is further modified for regulation.

8. The method for optimizing and controlling the performance of a high-temperature sintering furnace according to claim 7, characterized in that, The environmental factors-heating zone operating parameter correlation model is established by setting up temperature and humidity sensors, air pressure sensors and vibration sensors in the external environment of the high-temperature sintering furnace to collect ambient temperature, humidity, atmospheric pressure and equipment vibration data in real time.

9. The method for optimizing and controlling the performance of a high-temperature sintering furnace according to claim 4, characterized in that, The initial strategy for the high-temperature sintering furnace is determined by performing fusion processing based on the individual strategies of each heating zone and in conjunction with the heat transfer coefficient, including: Constructing the heat transfer coupling matrix of the heating zone ,in, This represents the heat transfer coefficient between the i-th heating zone and the j-th heating zone; Define the control parameter vector corresponding to the individual strategy for each heating zone. , This represents the p-th control parameter in the i-th heating zone; Establish a state-space model for the fusion strategy: in, This represents the temperature vector for each heating zone; The influence matrix of the control parameters; External interference matrix; This is the environmental disturbance vector; This is the vector of control parameters for all heating zones; Define the policy fusion objective function J: ; in, This is the temperature fluctuation vector; This is a preset temperature curve vector; , , These are the weighting coefficients; The objective function is solved using a convex optimization algorithm to obtain the globally optimal control parameter vector that satisfies the heat transfer coupling constraint. This forms the initial strategy for the high-temperature sintering furnace.

10. The method for optimizing and controlling the performance of a high-temperature sintering furnace according to claim 2, characterized in that, The fluctuation factors are related to heating element failure, airflow disturbance, and uneven heat conduction, while the main causes are related to heating element aging and insulation layer damage.

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