An experimental electric heating furnace temperature regulating system and method thereof

Abstract

This invention relates to the field of temperature control technology for experimental electric heating furnaces, and discloses a temperature control system and method for such furnaces. The system includes a material composition acquisition and judgment module and a temperature preset module, a three-dimensional temperature monitoring point array module, a graded temperature control execution module, and a main control module. By acquiring data on the composition content of the raw materials, a prediction model predicts the target sintering temperature curve. Simultaneously, temperature data is acquired through the main and auxiliary monitoring arrays, generating a three-dimensional temperature field thermogram with temperature change rates. The main control module employs a fuzzy adaptive PID algorithm to compare the changing trends of the target sintering temperature curve and the three-dimensional temperature field thermogram, generating a control strategy and sending it to the graded temperature control execution module. Point-to-point precise temperature control is achieved through temperature control components corresponding to the auxiliary monitoring array. This system ensures that the temperature field inside the furnace closely matches the target sintering temperature curve, improving the sintering effect.

Description

Technical Field

[0001] This invention relates to the field of temperature control technology for experimental electric heating furnaces, specifically to a temperature control system and method for an experimental electric heating furnace. Background Technology

[0002] Experimental electric heating furnaces are core equipment in material sintering and calcination experiments. Their temperature control precision, temperature field uniformity, and the compatibility of temperature profiles with the materials directly determine the microstructure, performance parameters, and reliability of the experimental results. However, existing experimental electric heating furnaces suffer from at least the following drawbacks: 1) The temperature profile configuration relies on manual experience and is preset as a fixed curve without adaptive adjustment based on the differences in key components of the raw materials. This results in poor adaptability between the temperature profile and the characteristics of the raw materials, easily leading to problems such as insufficient sintering and over-sintering, which affects the experimental results. At the same time, most of the previous sintering temperature parameters relied on manual experience prediction and calibration after multiple trial firings, which resulted in low efficiency and poor results.

[0003] 2) Temperature monitoring methods mostly use single-point monitoring, which cannot fully capture the distribution of the three-dimensional temperature field inside the furnace and the rate of temperature change. The monitoring data is one-sided and cannot reflect the true dynamics of the temperature field. It cannot meet the requirements of high-precision temperature control and cannot form data accumulation, which is not conducive to the subsequent analysis of sintering temperature results. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a temperature control system and method for an experimental electric heating furnace to solve the technical problems mentioned in the prior art.

[0005] A temperature control system for an experimental electric heating furnace, the system comprising: The material composition acquisition and temperature preset module includes a data acquisition unit, an intelligent prediction unit, and a curve storage library. The data acquisition unit is used to acquire the content data of key components of the raw materials. The intelligent prediction unit has a built-in prediction model trained based on a random forest and neural network fusion algorithm. The prediction model uses SHAP analysis to strengthen the weight of the content data of key components of the raw materials and automatically outputs the target sintering temperature curve and saves it to the curve storage library. The three-dimensional temperature monitoring point array module includes a built-in thermal analysis model and a main monitoring array unit and an auxiliary monitoring array unit located within the furnace heating chamber. The main monitoring array unit collects first temperature data of the temperature field within the furnace heating chamber in real time through multiple first temperature measurement points. The auxiliary monitoring array unit collects second temperature data of the temperature field within the furnace heating chamber in real time through at least one second temperature measurement point on the adjacent side of the main monitoring array unit. The thermal analysis model generates a three-dimensional temperature field thermal map based on the first temperature data and loads the temperature change rate into the three-dimensional temperature field thermal map based on the difference between the first and second temperature data per unit time. A graded temperature control execution module includes a temperature control component located within the heating chamber of the furnace body and corresponding to each of the auxiliary monitoring array units. The temperature control component comprises a heating unit and a cooling unit. The heating unit has several groups of electric heating tubes evenly distributed within the heating chamber of the furnace body. When the electric heating tubes are energized, they form a uniformly distributed temperature field within the heating chamber through thermal radiation, thermal conduction, and thermal convection. The cooling unit has a cold flow tube group located on one side of the electric heating tube groups. A cold medium is introduced into the cold flow tube group to exchange heat with the electric heating tube groups and the surrounding temperature field. The main control module is connected to the material composition acquisition and judgment and temperature preset module, the three-dimensional temperature monitoring point array module, and the graded temperature control execution module. The main control module is configured to: predict the changing trend of the three-dimensional temperature field thermogram based on the temperature change rate in the temperature field using a built-in fuzzy adaptive PID algorithm; and compare and analyze the changing trend of the predicted three-dimensional temperature field thermogram with the target sintering temperature curve configured for the current process through the data retrieval unit, generate a temperature control adjustment strategy, and send it to the graded temperature control execution module to maintain the changing trend of the temperature field according to the target sintering temperature curve configured for the current process.

[0006] Optionally, the main monitoring array unit has five first temperature measurement points located on the opposite side of the furnace door within the heating chamber of the furnace body, and the five first temperature measurement points are respectively located at the center and four corners of one side of the temperature field.

[0007] Optionally, the auxiliary monitoring array unit is provided in two sets, and the two sets of auxiliary monitoring array units are symmetrically arranged on opposite sides of the main monitoring array unit. Each set of auxiliary monitoring array units is provided with a second temperature measurement point at the cold input end and the hot output end of the temperature control component.

[0008] Optionally, the main control module further includes: The data receiving unit is used to receive the first temperature data and the second temperature data collected in real time by the three-dimensional temperature monitoring point array module. The logic operation unit calculates the rate of temperature change within the temperature field based on the difference between the first temperature data and the second temperature data per unit time and feeds it back to the heat map analysis model for dynamic updating; at the same time, it calculates the current temperature difference between the cold input end and the hot output end of any group of temperature control components in the second temperature data; and / or, calculates the average temperature difference between the cold input end and the hot output end of two groups of temperature control components in the second temperature data. The data analysis unit is configured to: generate a first temperature difference compensation strategy to adjust the cooling rate of the cold flow tube group corresponding to the temperature control component when the current temperature difference exceeds the set temperature difference allowable range; and generate a second temperature compensation strategy to adjust the heating power of the electric heating tube group corresponding to the temperature control component to balance local overheating when the average temperature difference exceeds a threshold. The instruction distribution unit is used to send the first temperature difference compensation strategy and the second temperature difference compensation strategy to the graded temperature control execution module; after the graded temperature control execution module finishes executing the first temperature difference compensation strategy and / or the second temperature difference compensation strategy, it generates a feedback signal and sends it to the instruction distribution unit to end the current temperature compensation measure. The early warning unit automatically triggers an early warning program to generate an early warning signal when the reception time of the feedback signal from the instruction distribution unit exceeds a threshold. The early warning program is to issue an early warning according to a customized early warning message.

[0009] Optionally, the temperature control adjustment strategy is set as follows: When the predicted trend of the three-dimensional temperature field thermogram with time-temperature change is higher than the target sintering temperature curve configured in the current process, the heating power of the electric heating tube group is continuously reduced and / or the cooling rate of the cold flow tube group is increased. When the predicted trend of the three-dimensional temperature field thermogram is lower than the target sintering temperature curve configured for the current process, the heating power of the electric heating tube group is continuously increased and / or the cooling rate of the cold flow tube group is reduced.

[0010] Optionally, the cold flow tube assembly includes a plurality of heat exchange tubes installed on the inner side wall of the heating chamber of the furnace body. The two ends of the heat exchange tubes extend to opposite sides of the heating chamber of the furnace body and are connected to a cold input pipe and a heat output pipe. The other ends of the cold input pipe and the heat output pipe penetrate the outer wall of the furnace body, and a cold medium input unit is installed at the air inlet end of the cold input pipe. The heat exchange tube is made of silicon carbide, and control valves are installed on the air inlet and air outlet sides of the heat exchange tube, respectively. The control valves are connected to the main control module.

[0011] Optionally, the electric heating tube assembly is configured with a U-shaped structure, and the electric heating tube assembly is a silicon molybdenum rod and a quartz tube; The heat exchange tubes are provided with inwardly recessed guide grooves on opposite sides, and the two ends of the open side of the electric heating tube assembly are respectively inserted into the guide grooves from one end of the heat exchange tube. The heating chamber of the furnace body has extension grooves on opposite sides of the worktable. The bottom of the electric heating tube group extends into the extension groove, and the top of the electric heating tube group penetrates the heating chamber of the furnace body and is connected to the main control module through a control circuit.

[0012] Optionally, the furnace door of the furnace body is provided with a temperature control self-locking structure, the temperature control self-locking structure comprising: A fixing part is provided on the opening side of the heating chamber of the furnace body. An electromagnetic adsorption component is installed on the side of the fixing part near the furnace door. The electromagnetic adsorption component is connected to the main control module through a drive circuit. An operating part is installed on the furnace door, and the side of the operating part closest to the fixing part is provided as a magnetic conductive part; The on / off control logic of the drive circuit is set as follows: when the first temperature data and / or the second temperature data exceed the safety threshold, the self-locking program is automatically triggered to connect the drive circuit. At this time, the electromagnetic adsorption component can adsorb the magnetic part to realize the furnace door self-locking.

[0013] A method for temperature control of an experimental electric heating furnace, applied to the system described above, the method comprising the following steps: S1. A prediction model is constructed by simulating and training multiple sets of empirical data based on a random forest and neural network fusion algorithm. S2. Obtain the key component content data of the raw materials and input it into the prediction model. The prediction model strengthens the weight of the key component content data of the raw materials through SHAP analysis, automatically outputs the target sintering temperature curve and saves it to the curve storage library. S3. Real-time acquisition of first and second temperature data of the internal temperature field of the heating chamber of the furnace body, generation of a three-dimensional temperature field thermogram based on the first temperature data, and generation of the temperature change rate of the three-dimensional temperature field thermogram based on the difference between the first and second temperature data per unit time. S4. Based on the fuzzy adaptive PID algorithm, predict the changing trend of the three-dimensional temperature field thermogram according to the rate of temperature change, and retrieve the target sintering temperature curve configured for the current process from the curve repository and compare it with the predicted changing trend of the three-dimensional temperature field thermogram to generate a temperature control adjustment strategy; control the temperature control component to execute the temperature control adjustment strategy to maintain the changing trend of the temperature field according to the target sintering temperature curve configured for the current process.

[0014] Optionally, the target sintering temperature curve is set as follows: Drying and preheating stage: heating from room temperature to 200-400℃ at a heating rate of 5-15℃ / min; First-stage roasting: heating from 200-400℃ to 800-1000℃ at a rate of 15-30℃ / min; Secondary roasting stage: heating from 800-1000℃ to 1300-1400℃ at a heating rate of 10-20℃ / min; Cooling and shaping stage: Cool to the preset temperature range at a rate of 5-15℃ / min.

[0015] The beneficial effects that this invention can produce include: 1. This invention, through the configuration of a predictive model, can automatically generate target sintering temperature curves based on the content data of key components in the raw materials. This weakens impurity interference and strengthens the influence of key components, significantly improving the adaptability of the temperature curve to the raw material characteristics. This avoids sintering defects caused by curve mismatch from the outset, ensuring the stability of experimental sample quality. Simultaneously, based on a closed-loop control system of material composition → temperature preset → real-time monitoring → dynamic adjustment, it continuously compares the temperature field trend with the target curve, dynamically adjusting heating / cooling parameters to reduce human intervention errors and improve the sintering uniformity of materials from different batches and locations. Furthermore, a distributed database records the application history of the curve and sintering effects, providing data support for continuous optimization of the predictive model, and the sintering stability gradually improves with long-term use.

[0016] 2. This invention employs a three-dimensional temperature monitoring point array design that combines a main monitoring array and an auxiliary monitoring array. By collecting temperature data from multiple points and dimensions, and using a thermal analysis model to generate a three-dimensional temperature field thermogram with the rate of temperature change, it comprehensively and realistically reflects the distribution and dynamic changes of the temperature field inside the furnace, providing accurate and comprehensive data support for subsequent temperature control and regulation.

[0017] 3. This invention achieves interlocked control of the heating and cooling units based on a temperature control adjustment strategy, enabling precise local regulation of different areas within the furnace, such as bidirectional temperature compensation. Simultaneously, the main control module generates a targeted temperature difference compensation strategy by calculating the local and average temperature differences, effectively balancing local temperature differences and avoiding the problem of uneven temperature field caused by overall control, ensuring that the temperature field within the furnace remains uniform and stable.

[0018] 4. This invention employs a fuzzy adaptive PID algorithm, which can predict the temperature field change trend based on the temperature change rate and compare it with the target sintering temperature curve in real time to quickly generate a temperature control adjustment strategy. This significantly improves the dynamic response speed of the temperature control system, achieves accurate matching between the temperature field change trend and the target curve, and the temperature control accuracy is significantly better than that of traditional temperature control systems.

[0019] 5. This invention, by configuring a temperature-controlled self-locking structure on the furnace door, automatically triggers a self-locking program when the furnace temperature exceeds a safety threshold, locking the furnace door via electromagnetic adsorption. This prevents accidents caused by accidental opening of the furnace door under high temperatures, providing reliable safety assurance for experimental operations and improving the system's operational safety. Simultaneously, the early warning unit triggers an alarm signal after temperature control compensation timeout, enhancing timely intervention and reducing experimental failures and material losses due to temperature runaway. Attached Figure Description

[0020] Figure 1 This is a block diagram of the architecture of an experimental electric heating furnace temperature control system according to the present invention; Figure 2 This is a schematic diagram of the furnace body structure of an experimental electric heating furnace temperature control system according to the present invention; Figure 3 In this invention Figure 2 A schematic diagram of the furnace door in the open position; Figure 4 In this invention Figure 3 A schematic diagram of the structure of the graded temperature control actuator module; Figure 5 In this invention Figure 3 A plan view of the furnace heating chamber; In the diagram: 1. Material composition acquisition and temperature preset module; 11. Data acquisition unit; 12. Intelligent prediction unit; 13. Curve storage library; 2. Three-dimensional temperature monitoring point array module; 21. Thermal analysis model; 22. Main monitoring array unit; 221. First temperature measurement point; 23. Auxiliary monitoring array unit; 231. Second temperature measurement point; 3. Graded temperature control execution module; 31. Heating unit; 311. Electric heating tube assembly; 32. Cooling unit; 321. Heat exchange tube; 322. 323 Cold input pipe, 324 Hot output pipe, 325 Cold medium input unit, 326 Control valve, 327 Guide groove, 4. Main control module, 41 Data receiving unit, 42 Data retrieval unit, 43 Logic operation unit, 44 Data analysis unit, 45 Command distribution unit, 46 Early warning unit, 5. Temperature control self-locking structure, 51 Fixing part, 511 Electromagnetic adsorption component, 52 Operating part, 521 Magnetic guide part, 53 Drive circuit, 6. Furnace body, 7. Furnace door. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Please see Figure 1As shown, this invention provides a temperature control system for an experimental electric heating furnace. The system includes a material composition acquisition and judgment and temperature preset module 1, a three-dimensional temperature monitoring point array module 2, a graded temperature control execution module 3, and a main control module 4. These modules are interconnected via a high-speed data bus, forming a closed-loop control link of "material characteristics → temperature preset → real-time monitoring → dynamic adjustment," ensuring that the temperature field inside the heating chamber of the furnace body 6 always conforms to the target sintering temperature curve, thus improving the sintering consistency and stability of the experimental materials. The material composition acquisition and judgment and temperature preset module 1 includes a data acquisition unit 11, an intelligent prediction unit 12, and a curve storage library 13. The data acquisition unit 11 integrates an X-ray fluorescence spectrometer and an electronic scale to acquire key component content data of the raw materials, such as the content of SiO2, Al2O3, and CaO in ceramsite sand. Simultaneously, the content data of each key component can be directly imported into the data acquisition unit 11 through manual input. The intelligent prediction unit 12 has a built-in prediction model trained using a random forest and neural network fusion algorithm. The prediction model uses SHAP analysis to strengthen the weight of key component content data of the raw materials, automatically outputs the target sintering temperature curve and saves it to the curve storage library 13 for easy retrieval and use, as well as customization of the target sintering temperature curve's variation parameters. The three-dimensional temperature monitoring point array module includes a built-in thermal map analysis model 21 and a main monitoring array unit 22 and an auxiliary monitoring array unit 23 located in the heating chamber of the furnace body 6. The main monitoring array unit 22 collects the first temperature data of the temperature field in the heating chamber of the furnace body 6 in real time through multiple first temperature measurement points 221; the auxiliary monitoring array unit 23 collects the second temperature data of the temperature field in the heating chamber of the furnace body 6 in real time through at least one second temperature measurement point 231 on the adjacent side of the main monitoring array unit 22; the thermal map analysis model 21 generates a three-dimensional temperature field thermal map based on the first temperature data, intuitively presenting the temperature distribution differences in the furnace, and loads the temperature change rate in the three-dimensional temperature field thermal map based on the difference between the first temperature data and the second temperature data per unit time. The main control module 4 connects to the material composition acquisition and judgment and temperature preset module 1, the three-dimensional temperature monitoring point array module 2, and the graded temperature control execution module 3. The main control module 4 is configured to: predict the changing trend of the three-dimensional temperature field thermogram based on the built-in fuzzy adaptive PID algorithm and the rate of temperature change within the temperature field; and compare and analyze the predicted changing trend of the three-dimensional temperature field thermogram with the target sintering temperature curve configured for the current process through the data retrieval unit 42, generating a temperature control adjustment strategy and sending it to the graded temperature control execution module 3 to maintain the changing trend of the temperature field according to the target sintering temperature curve configured for the current process. For example, Figure 3 and Figure 4As shown, the graded temperature control execution module 3 includes a temperature control component located in the heating chamber of the furnace body 6 and corresponding one-to-one with the auxiliary monitoring array unit 23, realizing point-to-point local control and overall temperature coordination, and improving temperature control accuracy. The temperature control component is provided with a heating unit 31 and a cooling unit 32. The heating unit 31 is provided with several groups of electric heating tubes 311 evenly distributed in the heating chamber of the furnace body 6. When the electric heating tubes 311 are energized, a uniformly distributed temperature field is formed in the heating chamber of the furnace body 6 through heat radiation, heat conduction and heat convection. The cooling unit 32 is provided with a cold flow tube group on one side of the electric heating tube group 311. A cold medium is introduced into the cold flow tube group to exchange heat with the electric heating tube group 311 and the surrounding temperature field.

[0023] In this embodiment, the curve repository 13 adopts a distributed database architecture to classify and store target sintering temperature curves corresponding to different material types and experimental purposes. It can support rapid curve retrieval, retrieval and updating, and at the same time record the application history and sintering effect of each target sintering temperature curve, providing data accumulation for subsequent prediction model optimization.

[0024] Furthermore, such as Figure 5 As shown, the main monitoring array unit 22 has five first temperature measurement points 221 located on the opposite side of the furnace door 7 within the heating chamber of the furnace body 6. These five first temperature measurement points 221 are respectively positioned at the center and four corners of one side of the temperature field. Specifically, the four corner points are located 5-10 cm from the side wall of the heating chamber and 5-10 cm from the top and bottom of the heating chamber. The first temperature measurement points 221 use PT100 platinum resistance temperature sensors with a temperature measurement range of -50℃ to 1600℃ and an error ≤ ±0.5℃. Temperature data from each first temperature measurement point 221 is collected in real time. During data processing, two output modes can be selected according to experimental requirements: in a normal scenario, the average of five sets of temperature data is used to ensure the accuracy of the overall temperature field; in a high-precision scenario, the average of the two sets of temperature data with the largest variance is used to highlight local temperature differences and avoid missing temperature anomalies.

[0025] Furthermore, such as Figure 5 As shown, two sets of auxiliary monitoring array units 23 are provided, and the two sets of auxiliary monitoring array units 23 are symmetrically arranged on opposite sides of the main monitoring array unit 22. Each set of auxiliary monitoring array units 23 has a second temperature measurement point 231 at the cold input end and the hot output end of the temperature control component, forming four key monitoring points. The second temperature measurement point 231 adopts a K-type thermocouple sensor with a response time ≤0.1s, which focuses on capturing the temperature changes in the area of ​​action of the temperature control component, providing data support for local temperature compensation.

[0026] Furthermore, such as Figure 1As shown, the main control module 4 also includes a data receiving unit 41, a logic operation unit 43, a data analysis unit 44, an instruction distribution unit 45, and an early warning unit 46. The data receiving unit 41 receives the first and second temperature data collected in real time by the three-dimensional temperature monitoring point array module 2. The logic operation unit 43 calculates the rate of temperature change within the temperature field based on the difference between the first and second temperature data within a unit time (1s to 2s) and feeds it back to the heat map analysis model 21 for dynamic updates. For example, the rate of temperature change is superimposed on the three-dimensional temperature field heat map with a color gradient to dynamically reflect the trend of temperature field changes, facilitating the main control module 4's prediction of temperature deviations. Simultaneously, it calculates the current temperature difference between the cold input and hot output ends of any set of temperature control components in the second temperature data; and / or, calculates the average temperature difference between the cold input and hot output ends of two sets of temperature control components in the second temperature data. The data analysis unit 44 is configured to: if the current temperature difference exceeds the set allowable temperature difference range, generate a first temperature difference compensation strategy to adjust the cold flow tube group of the corresponding temperature control component. The cooling rate can be adjusted by changing the input flow rate or velocity of the cooling medium in the cold flow tube group; and a second temperature compensation strategy can be generated when the average temperature difference exceeds a threshold to adjust the heating power of the electric heating tube group 311 of the corresponding temperature control component to balance local overheating; the instruction distribution unit 45 is used to send the first temperature difference compensation strategy and the second temperature difference compensation strategy to the graded temperature control execution module 3; after the graded temperature control execution module 3 finishes executing the first temperature difference compensation strategy and / or the second temperature difference compensation strategy, it generates a feedback signal and sends it to the instruction distribution unit 45 to end the current temperature compensation measure; the early warning unit 46 automatically triggers an early warning program to generate an early warning signal when the reception time of the feedback signal from the instruction distribution unit 45 exceeds a threshold. The early warning program is as follows: an early warning is issued according to the customized early warning information to remind relevant personnel that the system temperature control is abnormal and manual intervention is required, such as entering the manual temperature adjustment mode, which can reduce experimental failure and material loss caused by temperature runaway.

[0027] Furthermore, the temperature control strategy is set as follows: when the predicted change trend of the three-dimensional temperature field thermogram with time-temperature change is higher than the target sintering temperature curve configured for the current process, the heating power of the electric heating tube group 311 is continuously reduced and / or the cooling rate of the cold flow tube group is increased; when the predicted change trend of the three-dimensional temperature field thermogram with time-temperature change is lower than the target sintering temperature curve configured for the current process, the heating power of the electric heating tube group 311 is continuously increased and / or the cooling rate of the cold flow tube group is decreased.

[0028] Specifically, such as Figures 2 to 4As shown, the cold flow tube assembly includes 3 to 4 heat exchange tubes 321 installed side by side on the inner side wall of the heating chamber of the furnace body 6. The two ends of the heat exchange tubes 321 extend to opposite sides of the heating chamber of the furnace body 6 and are connected by a cold input pipe 322 and a heat output pipe 323. The other ends of the cold input pipe 322 and the heat output pipe 323 penetrate the outer wall of the furnace body 6. A cold medium input unit 324 is installed at the air inlet end of the cold input pipe 322. The cold medium input unit 324 includes a gas storage tank and a variable frequency silent induced draft fan installed at the gas outlet end of the gas storage tank, which can adjust the input rate of the cold medium. The gas storage tank contains inert cold media such as nitrogen and argon to prevent material oxidation. The heat exchange tube 321 is made of silicon carbide with a diameter of 10-15mm and a wall thickness of 2-3mm. Control valves 325, preferably electromagnetic proportional valves, are installed on the air inlet and outlet sides of the heat exchange tube 321. The control valves 325 are connected to the main control module 4 and can selectively open a corresponding number of electromagnetic proportional valves according to the cooling rate to change the input flow of the cold medium. At the same time, when the control valves 325 are closed, they can prevent the temperature in the heating chamber of the furnace body 6 from being lost through the cold flow tube group. The electric heating tube assembly 311 is designed with a U-shaped structure and consists of silicon molybdenum rods and quartz tubes. Guide grooves 326 are recessed inwards on both opposite sides of the heat exchange tube 321. The open ends of the electric heating tube assembly 311 are inserted into the guide grooves 326 from one end of the heat exchange tube 321, ensuring fixed positions and efficient heat transfer. This prevents bending and deformation of the electric heating tube assembly 311 after prolonged use, which could lead to inaccurate local temperature monitoring data. Extension grooves are provided on both opposite sides of the worktable within the heating chamber of the furnace body 6. The bottom of the electric heating tube assembly 311 extends into these extension grooves to provide a stable temperature field for the worktable in the heating chamber, ensuring uniform heating of the material. The top of the electric heating tube assembly 311 penetrates the heating chamber of the furnace body 6 and is connected to the main control module 4 via a control circuit, enabling stepless power adjustment. In the above, the temperature control strategy employs interlocking control between the cold flow tube assembly and the electric heating tube assembly 311 to achieve bidirectional temperature control, further improving temperature control accuracy.

[0029] In some embodiments, the electric heating tube assembly 311 is formed by a U-shaped structure consisting of a columnar silicon molybdenum rod and a quartz tube mounted on opposite sides of a fixed base. This allows the silicon molybdenum rod and quartz tube to jointly regulate the temperature field within the heating chamber. The control logic of the electric heating tube assembly 311 is configured as follows: during the drying preheating stage and the first-stage calcination stage, heating is achieved through the quartz tube, gradually raising the internal temperature of the heating chamber from room temperature to 800°C. Then, heating is switched to the second-stage calcination stage using the silicon molybdenum rod, raising the internal temperature of the heating chamber from 800°C to 1400°C. When the required calcination temperature of the material exceeds 1400°C, temperature compensation is achieved through simultaneous heating of the silicon molybdenum rod and quartz tube to meet the high-temperature heating requirements of the furnace body 6. This also ensures the service life of the electric heating tube assembly 311 and prevents damage or failure to reach the set heating temperature when the heating temperature of a single tube assembly exceeds the upper limit.

[0030] In other embodiments, the electric heating tube assembly 311 includes a U-shaped silicon molybdenum rod and a quartz tube, with the silicon molybdenum rod and the quartz tube arranged alternately, such as... Figure 4 As shown, a set of quartz tubes is placed between the two sets of silicon molybdenum rods and installed at equal intervals on one side of the heating chamber; at the same time, in order to ensure uniform heating inside the heating chamber, two sets of silicon molybdenum rods and one set of quartz tubes are symmetrically arranged on opposite sides of the heating chamber, so that the four sets of silicon molybdenum rods and two sets of quartz tubes together form a heating array to perform stepped uniform heating inside the heating chamber.

[0031] Furthermore, such as Figure 2 and Figure 3 As shown, a temperature-controlled self-locking structure 5 is provided on the furnace door 7 of the furnace body 6. The temperature-controlled self-locking structure 5 includes a fixing part 51 and an operating part 52. The fixing part 51 is located on the opening side of the heating chamber of the furnace body 6. An electromagnetic adsorption component 511 is installed on the side of the fixing part 51 near the furnace door 7. The electromagnetic adsorption component 511 is connected to the main control module 4 through a drive circuit 53. The operating part 52, such as a door handle, is installed on the furnace door 7. The side of the operating part 52 near the fixing part 51 is set as a magnetic conductive part 521. Specifically, the electromagnetic adsorption component 511 is set as an electromagnet, and the electromagnet has a groove that matches the shape of the magnetic conductive part 521, so that the magnetic conductive part 521 can be engaged into the groove to close the furnace door 7 during system shutdown. The on / off control logic of the drive circuit 53 is set as follows: when the first temperature data and / or the second temperature data exceed the safety threshold, the self-locking program is automatically triggered to connect the drive circuit 53. At this time, the electromagnetic adsorption component 511 can adsorb the magnetic part 521 to realize the self-locking of the furnace door 7, so as to avoid burns or material oxidation caused by opening the door under high temperature.

[0032] This invention also provides a temperature control method for an experimental electric heating furnace, which, when applied to the aforementioned system, enables precise control of the temperature field within the heating chamber of the furnace body 6. The method includes the following steps: Step S1: Simulation training is performed on multiple sets of empirical data using a random forest and neural network fusion algorithm to construct a prediction model. Specifically, ≥1000 sets of experimental data covering different material types (metals, ceramics, composite materials, etc.), different component ratios, and different sintering processes are collected. This includes the content of key raw material components, sintering temperature curve parameters such as heating rate, holding temperature, and holding time, as well as the corresponding sintering effects such as density, crystal structure, and mechanical properties. The basic prediction model is trained using a random forest and neural network fusion algorithm, and then the model parameters are optimized through SHAP analysis to strengthen the influence weight of key components on the temperature curve, ultimately forming a customized model with high prediction accuracy.

[0033] Step S2: Obtain the key component content data of the raw materials and input it into the prediction model. The prediction model strengthens the weight of the key component content data of the raw materials through SHAP (Shapely additive interpretation) analysis, automatically outputs the target sintering temperature curve and saves it to the curve storage library 13. For example, it highlights the sensitivity of the active component content to the heating rate and weakens the interference of minor impurities, thereby automatically outputting the target sintering temperature curve adapted to the current raw materials. The curve resolution reaches 1℃, ensuring the fine control of temperature. Step S3: Real-time acquisition of first temperature data and second temperature data of the internal temperature field of the heating chamber of furnace body 6; generation of a three-dimensional temperature field thermogram based on the first temperature data; and generation of the temperature change rate of the three-dimensional temperature field thermogram based on the difference between the first temperature data and the second temperature data per unit time. Step S4: Based on the fuzzy adaptive PID algorithm, predict the changing trend of the three-dimensional temperature field thermogram according to the rate of temperature change, and retrieve the target sintering temperature curve configured for the current process from the curve repository 13 and compare it with the predicted changing trend of the three-dimensional temperature field thermogram to generate a temperature control adjustment strategy; control the temperature control component to execute the temperature control adjustment strategy to maintain the changing trend of the temperature field according to the target sintering temperature curve configured for the current process.

[0034] In this embodiment, the target sintering temperature profile is set as follows: Drying and preheating stage: heating from room temperature to 200-400℃ at a heating rate of 5-15℃ / min; First-stage roasting: heating from 200-400℃ to 800-1000℃ at a rate of 15-30℃ / min; Secondary roasting stage: heating from 800-1000℃ to 1300-1400℃ at a heating rate of 10-20℃ / min; Cooling and shaping stage: Cool to a preset temperature range, such as room temperature, at a cooling rate of 5-15℃ / min.

Claims

1. A temperature control system for an experimental electric heating furnace, characterized in that, The system includes: The material composition acquisition and temperature preset module (1) includes a data acquisition unit (11), an intelligent prediction unit (12), and a curve storage library (13). The data acquisition unit (11) is used to acquire the content data of key components of the raw materials. The intelligent prediction unit (12) has a built-in prediction model trained based on the random forest and neural network fusion algorithm. The prediction model uses SHAP analysis to strengthen the weight of the content data of key components of the raw materials and automatically outputs the target sintering temperature curve and saves it to the curve storage library (13). The three-dimensional temperature monitoring point array module (2) includes a built-in heat map analysis model (21) and a main monitoring array unit (22) and an auxiliary monitoring array unit (23) located in the heating chamber of the furnace body (6). The main monitoring array unit (22) collects the first temperature data of the temperature field in the heating chamber of the furnace body (6) in real time through multiple first temperature measurement points (221). The auxiliary monitoring array unit (23) collects the second temperature data of the temperature field in the heating chamber of the furnace body (6) in real time through at least one second temperature measurement point (231) on the adjacent side of the main monitoring array unit (22). The heat map analysis model (21) generates a three-dimensional temperature field heat map based on the first temperature data, and loads the temperature change rate in the three-dimensional temperature field heat map based on the difference between the first temperature data and the second temperature data per unit time. A graded temperature control execution module (3) includes a temperature control component located in the heating chamber of the furnace body (6) and corresponding to the auxiliary monitoring array unit (23). The temperature control component is provided with a heating unit (31) and a cooling unit (32). The heating unit (31) is provided with several groups of electric heating tubes (311) evenly distributed in the heating chamber of the furnace body (6). When the electric heating tubes (311) are powered on, they form a uniformly distributed temperature field in the heating chamber of the furnace body (6) through heat radiation, heat conduction and heat convection. The cooling unit (32) is provided with a cold flow tube group on one side of the electric heating tube group (311). The cold flow tube group is circulated with a cold medium to exchange heat with the electric heating tube group (311) and the surrounding temperature field. The main control module (4) is connected to the material composition acquisition and judgment and temperature preset module (1), the three-dimensional temperature monitoring point array module (2) and the graded temperature control execution module (3). The main control module (4) is configured to: predict the change trend of the three-dimensional temperature field thermogram based on the built-in fuzzy adaptive PID algorithm according to the temperature change rate in the temperature field, and compare and analyze the change trend of the target sintering temperature curve configured in the current process with the predicted three-dimensional temperature field thermogram through the data retrieval unit (42), generate a temperature control adjustment strategy and send it to the graded temperature control execution module (3) to maintain the change trend of the temperature field according to the target sintering temperature curve configured in the current process.

2. The temperature control system for an experimental electric heating furnace according to claim 1, characterized in that, The main monitoring array unit (22) has five first temperature measurement points (221) located on the opposite side of the furnace door (7) in the heating chamber of the furnace body (6), and the five first temperature measurement points (221) are respectively located at the center and four corners of one side of the temperature field.

3. The temperature control system for an experimental electric heating furnace according to claim 1, characterized in that, The auxiliary monitoring array unit (23) is provided in two groups, and the two groups of auxiliary monitoring array units (23) are symmetrically arranged on opposite sides of the main monitoring array unit (22). Each group of auxiliary monitoring array units (23) is provided with a second temperature measurement point (231) at the cold input end and the hot output end of the temperature control component.

4. The temperature control system for an experimental electric heating furnace according to claim 3, characterized in that, The main control module (4) also includes: Data receiving unit (41), the data receiving unit (41) is used to receive the first temperature data and the second temperature data collected in real time by the three-dimensional temperature monitoring point array module (2); The logic operation unit (43) calculates the rate of temperature change in the temperature field based on the difference between the first temperature data and the second temperature data per unit time and feeds it back to the heat map analysis model (21) for dynamic updating; at the same time, it calculates the current temperature difference between the cold input end and the hot output end of any group of temperature control components in the second temperature data; and / or calculates the average temperature difference between the cold input end and the hot output end of two groups of temperature control components in the second temperature data. The data analysis unit (44) is configured to: generate a first temperature difference compensation strategy to adjust the cooling rate of the cold flow tube group corresponding to the temperature control component when the current temperature difference is identified to exceed the set temperature difference allowable range; and generate a second temperature compensation strategy to adjust the heating power of the electric heating tube group (311) corresponding to the temperature control component to balance local overheating when the average temperature difference is identified to exceed the threshold. The instruction distribution unit (45) is used to send the first temperature difference compensation strategy and the second temperature difference compensation strategy to the graded temperature control execution module (3); after the graded temperature control execution module (3) finishes executing the first temperature difference compensation strategy and / or the second temperature difference compensation strategy, it generates a feedback signal and sends it to the instruction distribution unit (45) to end the current temperature compensation measure. The warning unit (46) automatically triggers a warning program to generate a warning signal when the reception time of the feedback signal from the instruction distribution unit (45) exceeds a threshold. The warning program is to issue a warning according to the customized warning information.

5. The temperature control system for an experimental electric heating furnace according to claim 1, characterized in that, The temperature control strategy is set as follows: When the predicted trend of the three-dimensional temperature field thermogram is higher than the target sintering temperature curve configured by the current process, the heating power of the electric heating tube group (311) is continuously reduced and / or the cooling rate of the cold flow tube group is increased. When the predicted trend of the three-dimensional temperature field thermogram is lower than the target sintering temperature curve configured in the current process, the heating power of the electric heating tube group (311) is continuously increased and / or the cooling rate of the cold flow tube group is reduced.

6. The temperature control system for an experimental electric heating furnace according to claim 1, characterized in that, The cold flow tube assembly includes several heat exchange tubes (321) installed on the inner side wall of the heating chamber of the furnace body (6). The two ends of the heat exchange tubes (321) extend to opposite sides of the heating chamber of the furnace body (6) and are connected by a cold input pipe (322) and a heat output pipe (323). The other ends of the cold input pipe (322) and the heat output pipe (323) penetrate the outer wall of the furnace body (6), and a cold medium input unit (324) is installed at the air inlet end of the cold input pipe (322). The heat exchange tube (321) is made of silicon carbide. Control valves (325) are installed on the air inlet side and air outlet side of the heat exchange tube (321), and the control valves (325) are connected to the main control module (4).

7. The temperature control system for an experimental electric heating furnace according to claim 6, characterized in that, The electric heating tube assembly (311) is configured with a U-shaped structure, and the electric heating tube assembly (311) is a silicon molybdenum rod and a quartz tube; The heat exchange tube (321) has guide grooves (326) recessed inward on both opposite sides. The two ends of the electric heating tube group (311) on the open side are respectively inserted into the guide grooves (326) from one end of the heat exchange tube (321). The heating chamber of the furnace body (6) has extension grooves on opposite sides of the worktable. The bottom of the electric heating tube group (311) extends into the extension groove, and the top of the electric heating tube group (311) penetrates the heating chamber of the furnace body (6) and is connected to the main control module (4) through the control circuit.

8. The temperature control system for an experimental electric heating furnace according to claim 1, characterized in that, The furnace door (7) of the furnace body (6) is provided with a temperature control self-locking structure (5), the temperature control self-locking structure (5) includes: A fixing part (51) is provided on the opening side of the heating chamber of the furnace body (6). An electromagnetic adsorption component (511) is installed on the side of the fixing part (51) near the furnace door (7). The electromagnetic adsorption component (511) is connected to the main control module (4) through a drive circuit (53). An operating part (52) is installed on the furnace door (7), and the side of the operating part (52) near the fixing part (51) is provided as a magnetic conductive part (521). The on / off control logic of the drive circuit (53) is set as follows: when the first temperature data and / or the second temperature data exceed the safety threshold, the self-locking program is automatically triggered to connect the drive circuit (53). At this time, the electromagnetic adsorption component (511) can adsorb the magnetic part (521) to realize the self-locking of the furnace door (7).

9. A method for temperature control of an experimental electric heating furnace, applied to the system described in any one of claims 1-8, characterized in that, The method includes the following steps: S1. A prediction model is constructed by simulating and training multiple sets of empirical data based on a random forest and neural network fusion algorithm. S2. Obtain the key component content data of the raw materials and input it into the prediction model. The prediction model strengthens the weight of the key component content data of the raw materials through SHAP analysis, automatically outputs the target sintering temperature curve and saves it into the curve storage library (13). S3. Real-time acquisition of the first temperature data and the second temperature data of the internal temperature field of the heating chamber of the furnace body (6), generating a three-dimensional temperature field thermogram based on the first temperature data, and generating the temperature change rate of the three-dimensional temperature field thermogram based on the difference between the first temperature data and the second temperature data per unit time. S4. Based on the fuzzy adaptive PID algorithm, predict the changing trend of the three-dimensional temperature field thermogram according to the rate of temperature change, and retrieve the target sintering temperature curve configured for the current process from the curve repository (13) and compare it with the predicted changing trend of the three-dimensional temperature field thermogram to generate a temperature control adjustment strategy; control the temperature control component to execute the temperature control adjustment strategy to maintain the changing trend of the temperature field according to the target sintering temperature curve configured for the current process.

10. A method for temperature control of an experimental electric heating furnace according to claim 9, characterized in that, The target sintering temperature curve is set as follows: Drying and preheating stage: heating from room temperature to 200-400℃ at a heating rate of 5-15℃ / min; First-stage roasting: heating from 200-400℃ to 800-1000℃ at a rate of 15-30℃ / min; Secondary roasting stage: heating from 800-1000℃ to 1300-1400℃ at a heating rate of 10-20℃ / min; Cooling and shaping stage: Cool to the preset temperature range at a rate of 5-15℃ / min.

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