Self-adaptive temperature homogenization control method and device in gas collecting hood of silicon carbide furnace

Abstract

The invention discloses a self-adaptive temperature homogenization control method and device in a gas collecting hood of a silicon carbide furnace, and relates to the technical field of operation process control of environment-friendly facilities. The technical problems of difficulty in temperature field uniformity quantification, poor control adaptability and insufficient local optimization capability when a large totally-closed gas-collecting hood is adopted to cover a silicon carbide furnace to collect tail gas in the silicon carbide production process can be solved. The self-adaptive temperature homogenization control method in the silicon carbide furnace gas collecting hood comprises the steps that the real-time temperature of each preset temperature monitoring area in the silicon carbide furnace gas collecting hood is collected, the space temperature entropy is calculated according to the real-time temperature, and then the total exhaust flow of a draught fan is calculated; the fan exhaust flow distributed to each preset temperature monitoring area is calculated according to the fan exhaust total flow, the corresponding fan exhaust flow is used for extracting the tail gas with the temperature at the corresponding air outlet, so that self-adaptive temperature homogenization control is carried out, the real-time temperatures of the different preset temperature monitoring areas are uniform, and the real-time temperature uniformity of the different preset temperature monitoring areas is improved. The influence on the service life caused by non-uniform heating of the gas-collecting hood is avoided.

Description

Technical Field

[0001] This invention relates to the field of environmental protection facility operation process control technology, and in particular to an adaptive temperature uniformity control method and device for the gas collection hood of a silicon carbide furnace. Background Technology

[0002] Silicon carbide furnaces are typically used for smelting silicon carbide in open or semi-open environments. Approximately 90% of the exhaust gas is emitted without proper organization. This exhaust gas contains a large amount of harmful gases, making safe recovery extremely difficult. The current solution is to construct a large, enclosed gas collection hood that completely covers the production equipment. The enclosed gas collection hood has an air outlet connected to a fan. Once the fan is started, the exhaust gas is drawn out through the air outlet, thereby collecting the harmful gases generated inside the hood and transporting them to a purification treatment device for harmless disposal.

[0003] Because silicon carbide furnaces can be tens or even hundreds of meters long, the smelting reaction rates vary in different areas and sections, resulting in varying temperatures in the exhaust gases. Furthermore, different fan suction forces at different exhaust outlets lead to varying local negative pressures, causing localized overheating or underheating—a condition known as uneven temperature distribution. This uneven heating of the gas collecting hood causes tension damage, affecting its lifespan. Traditional temperature control methods typically use single-point or a few-point temperature feedback, which, due to the furnace length, is insufficient to accurately reflect the overall temperature distribution, easily leading to localized overheating or underheating.

[0004] In existing technologies, multi-point temperature control methods mainly suffer from the following problems: 1. The lack of effective quantitative indicators for temperature field uniformity makes it difficult to accurately assess temperature distribution. 2. The control strategies mostly adopt proportional-integral-derivative control with fixed parameters, which has poor adaptability and is difficult to cope with complex temperature field changes; 3. True local partition control cannot be achieved when there is only a single control condition output parameter. Summary of the Invention

[0005] In view of this, the present invention provides an adaptive temperature homogenization control method and device in the gas collecting hood of a silicon carbide furnace, which can solve the technical problems of difficulty in quantifying temperature field homogenization, poor control adaptability, and insufficient local optimization capability when using a large fully enclosed gas collecting hood to cover the silicon carbide furnace to collect tail gas in the silicon carbide production process.

[0006] According to one aspect of the present invention, an adaptive temperature homogenization control method is provided within the gas collecting hood of a silicon carbide furnace, the method comprising: Real-time temperature of each preset temperature monitoring area inside the gas collection hood of the silicon carbide furnace is collected; weight of each preset temperature monitoring area is calculated based on the real-time temperature; spatial temperature entropy is calculated based on the weight. The space temperature entropy is smoothed to obtain the smoothed temperature entropy, and the adaptive rate is calculated based on the smoothed temperature entropy. The total exhaust flow rate of the fan is calculated based on the adaptive rate and the temperature entropy after smoothing. The exhaust flow rate of the fan allocated to each of the preset temperature monitoring areas is then calculated based on the total exhaust flow rate of the fan to perform adaptive temperature uniformity control.

[0007] Preferably, the step of calculating the weight of each preset temperature monitoring zone based on the real-time temperature includes: The instantaneous average temperature is calculated based on the real-time temperature and the current discrete time ordinal number corresponding to the current discrete time. The current discrete time is obtained by multiplying the current discrete time ordinal number corresponding to the current discrete time by the sampling period. The real-time temperature of each preset temperature monitoring area at the current discrete time sequence is subtracted from the average instantaneous temperature to obtain a temperature difference. The temperature difference is then divided by the average instantaneous temperature to obtain the relative temperature difference of each preset temperature monitoring area at the current discrete time sequence. The weight of each preset temperature monitoring region is calculated based on the relative temperature difference for the current discrete time sequence.

[0008] Preferably, the step of calculating the spatial temperature entropy based on the weights includes: Calculate the logarithm of each of the weights; Calculate the product of the logarithm and the weight for the same preset temperature monitoring area to obtain the first product value for each preset temperature monitoring area; Calculate the first sum of all the first product values, and determine the spatial temperature entropy of the current discrete time sequence number by taking the negative of the first sum.

[0009] Preferably, the smoothing process of the spatial temperature entropy to obtain the smoothed temperature entropy includes: Calculate the initial spatial temperature entropy at the initial discrete time, and determine the initial spatial temperature entropy as the initial spatial temperature entropy after smoothing. Calculate the previous smoothed spatial temperature entropy of the previous discrete time sequence number based on the initial spatial temperature entropy after smoothing. Calculate the second product of the spatial temperature entropy and the smoothing coefficient, add the spatial temperature entropy after the previous smoothing process to the second product to obtain the second sum, calculate the third product of the spatial temperature entropy after the previous smoothing process and the smoothing coefficient, and subtract the third product from the second sum to obtain the smoothed temperature entropy of the current discrete time sequence.

[0010] Preferably, the step of calculating the adaptive rate based on the smoothed temperature entropy includes: The entropy change rate of the current discrete time sequence is calculated based on the spatial temperature entropy after the previous smoothing process, the temperature entropy after the smoothing process of the current discrete time sequence, and the sampling period. The adaptive rate is calculated based on the absolute value of the entropy change rate, the decay coefficient, and the basic adaptive rate.

[0011] Preferably, the step of calculating the total exhaust flow rate of the fan based on the adaptive rate and the smoothed temperature entropy includes: Calculate the first difference between the uniformity dead zone threshold and the smoothed temperature entropy after subtracting the current discrete time sequence number, and calculate the sign function value of the first difference; Calculate the product of the symbol function value, the adaptive rate, and the single-step exhaust flow increment to obtain the fourth product value. Calculate the total exhaust flow of the previous fan at the previous discrete time sequence number. Add the total exhaust flow of the previous fan to the fourth product value to obtain the total exhaust flow of the fan at the current discrete time sequence number.

[0012] Preferably, the step of calculating the fan exhaust flow rate allocated to each of the preset temperature monitoring zones based on the total fan exhaust flow rate includes: Determine whether the relative temperature difference of the preset temperature monitoring area at the current discrete time sequence is greater than 0. If it is, then the relative temperature difference is determined as the corresponding positive relative temperature difference. If not, then 0 is determined as the corresponding positive relative temperature difference. Calculate the positive weight based on the positive relative temperature difference. The fan exhaust flow rate of the corresponding preset temperature monitoring area is obtained by multiplying the positive weight of each preset temperature monitoring area by the total exhaust flow rate of the fan.

[0013] Preferably, the step of calculating the fan exhaust flow rate allocated to each of the preset temperature monitoring zones based on the total fan exhaust flow rate includes: The exhaust flow rate of the fan to be optimized in the preset temperature monitoring area is set as a variable, and the temperature to be adjusted in each preset temperature monitoring area with the current discrete time sequence is calculated based on the exhaust flow rate of the fan to be optimized. Obtain the instantaneous average temperature, calculate the sum of squares of the deviations between the temperature to be adjusted and the instantaneous average temperature, and determine the minimum value of the sum of squares of deviations as the objective function; Under the constraint that the exhaust flow rate of the fan to be optimized in each preset temperature monitoring area is non-negative and the sum of the exhaust flow rates of all the fans to be optimized is equal to the total exhaust flow rate of the fans, the exhaust flow rate of the fans in the preset temperature monitoring area is determined according to the objective function, wherein the exhaust flow rate of the fans is the optimal solution of the exhaust flow rate of the fans to be optimized.

[0014] Preferably, the step of calculating the temperature to be adjusted for each preset temperature monitoring area based on the exhaust flow rate of the fan to be optimized, using the current discrete time sequence number, includes: Determine the cooling coefficient for each of the preset temperature monitoring zones; Calculate the product of the exhaust flow rate of the fan to be optimized and the cooling coefficient to obtain the fifth product value; Obtain the zero fan exhaust flow temperature of each preset temperature monitoring area when the exhaust flow rate of the fan to be optimized is 0, calculate the zero fan exhaust flow temperature of the same preset temperature monitoring area minus the fifth product value to obtain the second difference, and determine the second difference as the temperature to be adjusted for each preset temperature monitoring area of ​​the current discrete time sequence.

[0015] According to another aspect of the present invention, an adaptive temperature homogenization control device is provided inside the gas collecting hood of a silicon carbide furnace, the device comprising: The data acquisition module is used to acquire the real-time temperature of each preset temperature monitoring area inside the gas collection hood of the silicon carbide furnace, calculate the weight of each preset temperature monitoring area based on the real-time temperature, and calculate the spatial temperature entropy based on the weight. The calculation module is used to smooth the space temperature entropy to obtain the smoothed temperature entropy, and calculate the adaptive rate based on the smoothed temperature entropy. The control module is used to calculate the total exhaust flow of the fan based on the adaptive rate and the temperature entropy after smoothing, and to calculate the exhaust flow of the fan allocated to each of the preset temperature monitoring areas based on the total exhaust flow of the fan, so as to perform adaptive temperature uniformity control.

[0016] By employing the above technical solution, the present invention provides an adaptive temperature uniformity control method and device for a silicon carbide furnace gas collecting hood. The method involves collecting the real-time temperature of each preset temperature monitoring area within the silicon carbide furnace gas collecting hood, calculating the weight of each preset temperature monitoring area based on the real-time temperature, calculating the spatial temperature entropy based on the weight, smoothing the spatial temperature entropy to obtain a smoothed temperature entropy, calculating an adaptive rate based on the smoothed temperature entropy, calculating the total exhaust flow rate of the fan based on the adaptive rate and the smoothed temperature entropy, calculating the fan exhaust flow rate allocated to each preset temperature monitoring area based on the total fan exhaust flow rate, and using the corresponding fan exhaust flow rate to extract tail gas carrying temperature from the corresponding air outlet for adaptive temperature uniformity control. This ensures that the real-time temperature of different preset temperature monitoring areas is uniform, avoiding uneven heating of the gas collecting hood and affecting its service life. Using spatial temperature entropy as a quantitative indicator of temperature field uniformity can accurately assess temperature distribution. By dynamically adjusting the adaptive rate of the fan exhaust, a balance can be achieved between rapid response and stability, resulting in strong adaptability. Finally, under a single control output condition (i.e., a single adjustment of the fan exhaust flow rate), local optimization can be achieved through allocation without additional hardware costs.

[0017] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0018] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of this application. In the drawings: Figure 1 A schematic flowchart of an adaptive temperature homogenization control method for a silicon carbide furnace gas collecting hood provided by an embodiment of the present invention is shown. Figure 2 A schematic flowchart of another adaptive temperature homogenization control method in the gas collecting hood of a silicon carbide furnace provided by an embodiment of the present invention is shown. Figure 3 This invention provides a schematic diagram of the structure of an adaptive temperature homogenization control device inside the gas collecting hood of a silicon carbide furnace. Figure 4 A schematic diagram of another adaptive temperature homogenization control device for a silicon carbide furnace gas collecting hood provided in an embodiment of the present invention is shown. Detailed Implementation

[0019] The present invention will be described in detail below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0020] This embodiment provides an adaptive temperature homogenization control method within the gas collecting hood of a silicon carbide furnace, such as... Figure 1 As shown, the method includes: 101. Collect the real-time temperature of each preset temperature monitoring area inside the gas collection hood of the silicon carbide furnace, calculate the weight of each preset temperature monitoring area based on the real-time temperature, and calculate the spatial temperature entropy based on the weight.

[0021] Specifically, for collecting the real-time temperature of each preset temperature monitoring area within the gas collecting hood of the silicon carbide furnace, the preset temperature monitoring areas include: One, arranged inside the gas collecting hood of the silicon carbide furnace. Each temperature sensor corresponds to a preset temperature monitoring area. The preset temperature monitoring area can be preset according to the position of the air outlet of the air collection hood. For example, a circle with the center of the air outlet as the center and a preset length as the radius is used as the preset temperature monitoring area corresponding to the air outlet.

[0022] Using spatial temperature entropy as a quantitative indicator of temperature field uniformity can accurately assess temperature distribution.

[0023] 102. Smooth the space temperature entropy to obtain the smoothed temperature entropy, and calculate the adaptive rate based on the smoothed temperature entropy.

[0024] To suppress measurement noise, the spatial temperature entropy is smoothed. Then, an adaptive rate is calculated based on the smoothed temperature entropy. This adaptive rate is the adaptive rate of the fan exhaust; the higher the fan exhaust rate, the greater the amount of exhaust gas carrying temperature is drawn from the outlet, all other things being equal. The purpose of calculating the adaptive rate is to ensure that, as the temperature entropy changes after smoothing, the adaptive rate, being based on the smoothed temperature entropy, will change with the smoothed temperature entropy, thus achieving dynamic adjustment of the adaptive rate. By dynamically adjusting the adaptive rate, a balance is achieved between rapid response and stability.

[0025] 103. Calculate the total exhaust flow rate of the fan based on the adaptive rate and the temperature entropy after smoothing, and calculate the exhaust flow rate of the fan allocated to each of the preset temperature monitoring areas based on the total exhaust flow rate of the fan, so as to perform adaptive temperature uniformity control.

[0026] In specific application scenarios, the total exhaust flow of the fan is controlled and distributed among various preset temperature monitoring areas, and each preset temperature monitoring area is allocated a corresponding exhaust flow of the fan, thereby making the temperature of each preset temperature monitoring area uniform.

[0027] As one implementation method, a virtual local flow allocation strategy is used to allocate the total exhaust flow of the fan according to the weight of each preset temperature monitoring area. This allocation method ensures that the high-temperature area receives more exhaust flow from the fan, thereby extracting more exhaust gas carrying temperature from the corresponding air outlet, while the low-temperature area receives less exhaust flow from the fan, thereby extracting less exhaust gas carrying temperature from the corresponding air outlet, thus achieving the effect of algorithm-level local partitioning.

[0028] This invention provides an adaptive temperature uniformity control method and apparatus for a silicon carbide furnace gas collecting hood. The method involves collecting the real-time temperature of each preset temperature monitoring area within the gas collecting hood, calculating the weight of each preset temperature monitoring area based on the real-time temperature, and calculating the spatial temperature entropy based on the weight. The spatial temperature entropy is then smoothed to obtain a smoothed temperature entropy, and an adaptive rate is calculated based on the smoothed temperature entropy. The total exhaust flow rate of the fan is calculated based on the adaptive rate and the smoothed temperature entropy, and the fan exhaust flow rate allocated to each preset temperature monitoring area is calculated based on the total exhaust flow rate. The corresponding fan exhaust flow rate is used to extract tail gas carrying temperature from the corresponding air outlet for adaptive temperature uniformity control. This ensures that the real-time temperature of different preset temperature monitoring areas is uniform, preventing uneven heating of the gas collecting hood and affecting its service life. Using spatial temperature entropy as a quantitative indicator of temperature field uniformity can accurately assess temperature distribution. By dynamically adjusting the adaptive rate of the fan exhaust, a balance can be achieved between rapid response and stability, resulting in strong adaptability. Finally, under a single control output condition (i.e., a single adjustment of the fan exhaust flow rate), local optimization can be achieved through allocation without additional hardware costs.

[0029] Furthermore, as a refinement and extension of the specific implementation methods of the above embodiments, in order to fully illustrate the specific implementation process of this embodiment, another adaptive temperature homogenization control method within the gas collecting hood of a silicon carbide furnace is provided, such as... Figure 2 As shown, the method includes: 201. Collect the real-time temperature of each preset temperature monitoring area inside the gas collection hood of the silicon carbide furnace, calculate the weight of each preset temperature monitoring area based on the real-time temperature, and calculate the spatial temperature entropy based on the weight.

[0030] The sampling period is The real-time temperature is the temperature at the current discrete moment, and the current discrete moment is... ,in, It is the ordinal number of the current discrete time corresponding to the current discrete time. It is a positive integer greater than or equal to 1. Each preset temperature monitoring area corresponds to the current discrete time ordinal number at the current discrete time. The measured real-time temperature is recorded as , i=1,...,n.

[0031] The step of calculating the weight of each preset temperature monitoring area based on the real-time temperature includes: calculating the average instantaneous temperature of the current discrete time ordinal number corresponding to the current discrete time based on the real-time temperature, wherein the current discrete time ordinal number corresponding to the current discrete time is multiplied by the sampling period to obtain the current discrete time; calculating the real-time temperature of each preset temperature monitoring area of ​​the current discrete time ordinal number minus the average instantaneous temperature to obtain a temperature difference value; calculating the temperature difference value divided by the average instantaneous temperature to obtain the relative temperature difference of each preset temperature monitoring area of ​​the current discrete time ordinal number; and calculating the weight of each preset temperature monitoring area of ​​the current discrete time ordinal number based on the relative temperature difference.

[0032] It should be noted that the current discrete time sequence number corresponds to the current discrete time. Multiply by the sampling period Get the current discrete time For example, sampling period It lasts for 10 minutes. When it is 1, the actual time of the current discrete moment is 10 minutes. When it is 2 o'clock, the actual time of the current discrete moment is 20 minutes.

[0033] Because of the sampling period It is fixed; to simplify the formula intuitively, the current discrete time sequence number is used. As a representation of the actual time at the current discrete moment, for example Represents the current discrete time sequence number This represents the current discrete moment. The average instantaneous temperature over this actual time period. Represents the current discrete time sequence number This represents the current discrete moment. This is the actual spatial temperature entropy over time.

[0034] Current discrete time sequence number Instantaneous average temperature :

[0035] Current discrete time sequence number Preset temperature monitoring area relative temperature difference :

[0036] The influence of dimensions is eliminated by relative temperature difference, and .

[0037] Current discrete time sequence number Preset temperature monitoring area weight :

[0038] Since the sum of the weights is 1, if there exists a current discrete time sequence number... If the relative temperature difference between the n preset temperature monitoring areas is all 0, then the current discrete time sequence number... The weights of the n preset temperature monitoring areas are all 0, which obviously does not meet the requirement that the sum of the weights is 1. Therefore, there is no current discrete time sequence number. The case where the relative temperature difference of the n preset temperature monitoring areas is all 0, and the weights The denominator is the current discrete time sequence number. The weights are the sum of the absolute values ​​of the relative temperature differences among the n preset temperature monitoring areas; therefore, the denominator of the weights must not be zero. Furthermore, since the spatial temperature entropy needs to be calculated subsequently... Therefore, each preset temperature monitoring area weight All are greater than 0.

[0039] The step of calculating the spatial temperature entropy based on the weights includes: calculating the logarithm of each weight; calculating the product of the logarithm of the same preset temperature monitoring area and the weight to obtain a first product value for each preset temperature monitoring area; calculating a first sum of all the first product values, and determining the negative of the first sum as the spatial temperature entropy of the current discrete time sequence.

[0040] Specifically, the logarithm of the weights is the base e.

[0041] Spatial temperature entropy of the current discrete time ordinal number :

[0042] in, It is the space temperature entropy, which is the space temperature entropy. As a quantitative indicator of temperature uniformity, the spatial temperature entropy is the quantified value of temperature field uniformity. The formula for spatial temperature entropy shows that it is an increasing function of the uniformity of the weight distribution. The more uniform the weight distribution, the more uniform the temperature, and the greater the spatial temperature entropy. Conversely, the less uniform the weight distribution, the less uniform the temperature, and the smaller the spatial temperature entropy. For example, when all preset temperature monitoring areas are equal to 1 / n, the spatial temperature entropy... That is, the weight distribution is completely uniform, the temperature distribution is completely uniform, and the spatial temperature entropy is maximized; when the weight of one preset temperature monitoring area approaches 1, and the weights of other preset temperature monitoring areas all approach 0 (each preset temperature monitoring area) weight The range of the spatial temperature entropy is greater than 0, meaning the weight distribution is uneven, the temperature distribution is uneven, and the spatial temperature entropy approaches 0. Therefore, the range of the spatial temperature entropy is greater than 0 and less than or equal to 0. .

[0043] 202. The space temperature entropy is smoothed to obtain the smoothed temperature entropy.

[0044] In one implementation method, to suppress the interference of industrial field measurement noise on the control system and ensure control stability, the spatial temperature entropy is smoothed. The smoothing process is a first-order exponential smoothing. The smoothing process of the spatial temperature entropy to obtain the smoothed temperature entropy includes: calculating the initial spatial temperature entropy at the initial discrete time; determining the initial spatial temperature entropy as the smoothed initial spatial temperature entropy; calculating the previous smoothed spatial temperature entropy at the previous discrete time ordinal based on the smoothed initial spatial temperature entropy; calculating the second product of the spatial temperature entropy and the smoothing coefficient; adding the previous smoothed spatial temperature entropy to the second product to obtain a second sum; calculating the third product of the previous smoothed spatial temperature entropy and the smoothing coefficient; and subtracting the third product from the second sum to obtain the smoothed temperature entropy at the current discrete time ordinal.

[0045] Wherein, the current discrete time sequence number is The ordinal number of the previous discrete time step is The current discrete time ordinal number corresponds to the current discrete time. The previous discrete time step corresponding to the ordinal number of the previous discrete time step is .

[0046] It should be noted that the current discrete time sequence number It is greater than or equal to 1, that is, the ordinal number of the current discrete time. The previous discrete moment corresponding to the current discrete moment is the initial discrete moment. The calculation of the initial spatial temperature entropy at the initial discrete moment includes: obtaining each preset temperature monitoring area at the initial discrete moment. initial temperature Calculate the average initial instantaneous temperature for all initial temperatures, and obtain Each preset temperature monitoring zone is calculated based on the initial instantaneous average temperature and the initial temperature. initial relative temperature difference Calculate the temperature monitoring area for each preset temperature zone based on the initial relative temperature difference. The initial weights are used to calculate the preset temperature monitoring area. The initial space temperature entropy.

[0047] Preset temperature monitoring area initial relative temperature difference :

[0048] Preset temperature monitoring area initial weights :

[0049] Preset temperature monitoring area initial space temperature entropy :

[0050] The initial space temperature entropy is determined to be the initial space temperature entropy after smoothing, i.e. , It is the initial space temperature entropy after smoothing.

[0051] Based on the initial space temperature entropy after the smoothing process Calculate the current discrete time sequence number The previous discrete time sequence number The space temperature entropy after the previous smoothing process Calculate the second product of the spatial temperature entropy and the smoothing coefficient. The second sum is obtained by adding the spatial temperature entropy after the previous smoothing process to the second product value. Calculate the third product of the spatial temperature entropy after the previous smoothing process and the smoothing coefficient. The second sum Subtract the third product value The smoothed temperature entropy of the current discrete time sequence number is obtained. .

[0052] That is, the following formula:

[0053] in, It is a smoothing coefficient used to suppress measurement noise. It is the spatial temperature entropy after the previous smoothing process. It is the temperature entropy after smoothing. It is the temperature entropy of space.

[0054] If the current discrete time sequence number If it is 1, then the ordinal number of the previous discrete time step If it is 0, calculate the current discrete time sequence number. It is 1 o'clock : ,in, Spatial temperature entropy based on the current discrete time sequence The formula for calculation, that is ,Depend on and Calculated .

[0055] If the current discrete time sequence number If it is 2, then the ordinal number of the previous discrete time step is... It is 1, calculate the current discrete time sequence number. It is 2 o'clock : ,in, Spatial temperature entropy based on the current discrete time sequence The formula for calculation, that is , ,Depend on and Calculated .

[0056] For the current discrete time sequence number Cases greater than 2 are not listed here.

[0057] 203. Calculate the adaptive rate based on the temperature entropy after the smoothing process.

[0058] The step of calculating the adaptive rate based on the smoothed temperature entropy includes: calculating the entropy change rate of the current discrete time sequence based on the previous smoothed spatial temperature entropy, the smoothed temperature entropy of the current discrete time sequence, and the sampling period; and calculating the adaptive rate based on the absolute value of the entropy change rate, the attenuation coefficient, and the basic adaptive rate.

[0059] Current discrete time sequence number rate of change of entropy :

[0060] in, It is the sampling period. It is the spatial temperature entropy after the previous smoothing process. It is the temperature entropy after smoothing.

[0061] The adaptive rate is calculated from the absolute value of the rate of change of entropy; that is, the adaptive rate is dynamically adjusted based on the absolute value of the rate of change of entropy. :

[0062] in, It is the current discrete time sequence number. rate of change of entropy It is the basic adaptive rate. It is the attenuation coefficient. When the absolute value of the rate of change of entropy... When large, adaptive rate Automatic reduction to avoid oscillation; when the system approaches steady state... Restore rapid response.

[0063] 204. Calculate the total exhaust flow rate of the fan based on the adaptive rate and the temperature entropy after smoothing.

[0064] In this embodiment, calculating the total exhaust flow rate of the fan based on the adaptive rate and the smoothed temperature entropy includes: calculating the uniformity dead zone threshold. Subtract the current discrete time sequence number Temperature entropy after smoothing The first difference is used to calculate the sign function value of the first difference. ; Calculate the symbolic function value The adaptive rate Single-step exhaust flow increment The product of these values ​​is used to obtain the fourth product value, and the sequence number of the previous discrete time step is calculated. Total exhaust flow of the previous fan The total exhaust flow rate of the previous fan Adding this to the fourth product value yields the total exhaust flow rate of the fan at the current discrete time sequence. .

[0065] Wherein, the current discrete time sequence number The total exhaust flow rate of the fan is , It is the maximum value of the total exhaust flow of the fan.

[0066] Based on adaptive control law with dead zone:

[0067] in, The uniformity dead zone threshold; This represents the incremental exhaust flow rate in a single step. It is the current discrete time sequence number. Temperature entropy after smoothing It is the ordinal number of the previous discrete time step. The corresponding total exhaust flow rate of the previous fan, It is an adaptive rate, which enables the controller to automatically reduce the adjustment step size to avoid oscillation when the temperature field changes drastically, and to restore its fast response capability in steady state. It is the total exhaust flow rate of the fan at the current discrete time sequence.

[0068]

[0069] Where sign is the sign function. The dead zone is half the width.

[0070] It should be noted that the core of the adaptive adjustment mechanism lies in monitoring system state changes in real time through the rate of entropy change. When the system temperature distribution tends to be uniform, the spatial temperature entropy... Increase, rate of change of entropy It is a positive value; when the system temperature distribution tends to be non-uniform, Decrease, rate of change of entropy Negative values. Adaptive rate. Using the absolute value of the rate of change of entropy As input, dynamic adjustment is achieved through an exponential decay relationship: regardless of whether the system is in an improving or deteriorating state, as long as the entropy change rate... Increase by Know, Automatically reduce to avoid oscillation; when the system approaches steady state, When approaching zero, Restore to basic adaptive rate To ensure a rapid response.

[0071] This dynamic adjustment mechanism, based on the absolute value of the rate of entropy change, can calculate whether the total exhaust flow of the fan should be increased or decreased at the current discrete moment compared to the previous discrete moment, and by what extent. Specifically: Based on the temperature entropy after smoothing Deviation from uniformity dead zone threshold Size determination The sign of the sign is used to determine middle compared to Whether to increase or decrease, that is, whether the total exhaust flow rate of the fan should be increased or decreased at the current discrete moment compared to the previous discrete moment, and based on the adaptive rate. The value is calculated to show the degree of change in the total exhaust flow rate of the fan compared to the previous discrete moment.

[0072] In summary, the total exhaust flow of the fan at the current discrete moment is adjusted compared to the previous discrete moment through an adaptive adjustment mechanism.

[0073] 205a. Determine whether the relative temperature difference of the preset temperature monitoring area at the current discrete time sequence is greater than 0. If yes, determine the relative temperature difference as the corresponding positive relative temperature difference. If no, determine 0 as the corresponding positive relative temperature difference. Calculate the positive weight based on the positive relative temperature difference. Multiply the positive weight of each preset temperature monitoring area by the total exhaust flow of the fan to obtain the exhaust flow of the corresponding preset temperature monitoring area for adaptive temperature uniformity control.

[0074] As one implementation method, to distinguish the direction of temperature deviation, specifically, for the current discrete time sequence, if the relative temperature difference of a certain preset temperature monitoring area is greater than 0, it indicates that the real-time temperature is greater than the instantaneous average temperature, and the relative temperature difference of this preset temperature monitoring area is determined as a positive relative temperature difference (this preset temperature monitoring area is then regarded as a high-temperature area). If the relative temperature difference of a certain preset temperature monitoring area is less than or equal to 0, it indicates that the real-time temperature is less than or equal to the instantaneous average temperature, and 0 is determined as the positive relative temperature difference of this preset temperature monitoring area. The positive relative temperature difference is expressed by the following formula:

[0075] in, It is a positive relative temperature difference. It is a relative temperature difference.

[0076] The positive weight is calculated based on the positive relative temperature difference.

[0077]

[0078] in, It is a positive weight.

[0079] In practical application scenarios, there is no situation where the relative temperature difference of all preset temperature monitoring areas is less than 0 (that is, there is no situation where the actual temperature of all preset temperature monitoring areas is less than the instantaneous average temperature), nor is there a situation where the relative temperature difference of all preset temperature monitoring areas is equal to 0 (as discussed in step 201 of the embodiment, and will not be repeated here). Therefore, there is no situation where the positive relative temperature difference of all preset temperature monitoring areas is equal to 0, that is, the sum of the positive relative temperature differences of all preset temperature monitoring areas is greater than 0. Therefore, the denominator of the positive weight must not be 0.

[0080] The reason why there is no situation where the relative temperature difference of all preset temperature monitoring areas is less than 0 is as follows: Firstly, the instantaneous average temperature is calculated based on the average of the actual temperatures of all preset temperature monitoring areas. Secondly, in actual application scenarios, if the actual temperature of a preset temperature monitoring area is less than the instantaneous average temperature, it is not necessary to allocate a corresponding fan exhaust flow rate to that preset temperature monitoring area. This is because the purpose of allocating a fan exhaust flow rate to a preset temperature monitoring area is that it is a high-temperature area, and the exhaust gas with temperature should be discharged to reduce the temperature. However, in reality, the preset temperature monitoring area is not a high-temperature area, so it is not necessary to allocate a corresponding fan exhaust flow rate to that preset temperature monitoring area. This is also the reason why positive weighting, rather than weighting, is used when allocating the corresponding fan exhaust flow rate in this embodiment.

[0081] Based on the positive weight of each of the preset temperature monitoring areas Multiply by the total exhaust flow rate of the aforementioned fan The corresponding preset temperature monitoring area is obtained. Fan exhaust flow rate That is, the total exhaust flow of the fan is allocated to each preset temperature monitoring zone according to the positive weight.

[0082] Preset temperature monitoring area The exhaust flow rate of the fan is ,satisfy:

[0083] Specifically, , It is a positive weight. It is the total exhaust flow rate of the fan. It is the exhaust flow rate of the fan.

[0084] Example: Temperature homogenization control in silicon carbide smelting furnaces: Application scenario: A silicon carbide smelting furnace has internal dimensions of 2m×1m×1m, and the temperature is required to be controlled within the range of 800±5℃, with a temperature uniformity requirement of ±10℃. Hardware configuration: Temperature sensor: 16 K-type thermocouples, evenly distributed inside the furnace; sampling period: Second, Control output: Variable frequency speed control for exhaust fan, flow range 0-100%, parameter settings: smoothness coefficient: Basic adaptive rate: Attenuation coefficient: Single-step exhaust flow rate increment: Uniformity dead zone threshold: Dead zone half width: .

[0085] Control process: 1. Initialization phase: When the system starts, all parameters are initialized. , 2. Steady-state operation phase: 16 real-time temperature readings are collected every 1 second. Calculate the instantaneous average temperature and relative temperature difference Calculate weights and space temperature entropy The temperature entropy of space is smoothed to obtain the smoothed temperature entropy. Calculate the total exhaust flow rate of the fan. Calculate the exhaust flow rate of the fan. 3. Disturbance Response Stage: When a localized heat source disturbance occurs inside the furnace, the preset temperature monitoring area... Positive relative temperature difference Increase, positive weight This increases the amount of exhaust airflow allocated to the pre-set temperature monitoring area, thus reducing the space temperature entropy. As the flow rate decreases, the controller automatically increases the total exhaust flow of the fan.

[0086] Control performance: Temperature uniformity improved from the initial ±25℃ to ±8℃; Response time: approximately 3-5 minutes from the occurrence of disturbance to the return to uniformity; Overshoot: less than 2℃; Steady-state error: less than 1℃.

[0087] Among them, when local heat source disturbances occur inside the furnace, a preset temperature monitoring area is set. Positive relative temperature difference Increase, positive weight This increases the amount of exhaust airflow allocated to the pre-set temperature monitoring area, thus reducing the space temperature entropy. As the temperature decreases, the controller automatically increases the total exhaust flow of the fan. It should be noted that the formula for calculating the positive weight has a clear monotonicity: when a certain preset temperature monitoring area... When the positive relative temperature difference of other preset temperature monitoring areas increases while the relative temperature difference remains constant, the numerator increases linearly. Although the denominator also increases due to the inclusion of this incremental term, the summation term in the denominator... It encompasses the positive relative temperature difference across all regions, thus its increase is relatively small, achieving the effect that an increase in the positive relative temperature difference leads to an increase in the positive weight. Mathematical derivation proves that for any region... ,when There will always be a time when... This ensures that the weighting ratio strictly follows the degree of temperature deviation.

[0088] 205b. Set the exhaust flow rate of the fan to be optimized in the preset temperature monitoring area as a variable, and calculate the temperature to be adjusted for each preset temperature monitoring area with the current discrete time sequence based on the exhaust flow rate of the fan to be optimized.

[0089] It should be noted that steps 201, 202, 203, 204, and 205a of the embodiment are one implementation scheme, and steps 201, 202, 203, 204, 205b, 206b, and 207b of the embodiment are an implementation scheme parallel to it.

[0090] The step of calculating the temperature to be adjusted for each preset temperature monitoring region at the current discrete time sequence based on the exhaust flow rate of the fan to be optimized includes: determining the cooling coefficient of each preset temperature monitoring region; calculating the product of the exhaust flow rate of the fan to be optimized and the cooling coefficient to obtain a fifth product value; obtaining the zero fan exhaust flow temperature of each preset temperature monitoring region when the exhaust flow rate of the fan to be optimized is 0; calculating the zero fan exhaust flow temperature of the same preset temperature monitoring region minus the fifth product value to obtain a second difference value; and determining the second difference value as the temperature to be adjusted for each preset temperature monitoring region at the current discrete time sequence. The formula is as follows:

[0091] in, It is the exhaust flow rate and temperature of the zero fan. The exhaust flow rate of the fan needs to be optimized. It refers to the cooling coefficient, which reflects the degree to which changes in the exhaust flow rate of a fan affect the temperature. For example, the higher the cooling coefficient, the greater the temperature drop per unit change in the exhaust flow rate of the fan. It is the second difference, and also the preset temperature monitoring area. The temperature to be adjusted.

[0092] It should be noted that the temperature to be adjusted is different from the real-time temperature in step 201 of the embodiment. The temperature to be adjusted is expressed by an expression based on the variable of the exhaust flow rate of the fan to be optimized, while the real-time temperature is specific data.

[0093] 206b. Obtain the instantaneous average temperature, calculate the sum of squares of the deviations between the temperature to be adjusted and the instantaneous average temperature, and determine the minimum value of the sum of squares of the deviations as the objective function.

[0094] 207b. Under the constraint that the exhaust flow rate of the fan to be optimized in each preset temperature monitoring area is non-negative and the sum of the exhaust flow rates of all the fans to be optimized is equal to the total exhaust flow rate of the fans, the exhaust flow rate of the fans in the preset temperature monitoring area is determined according to the objective function to perform adaptive temperature uniformity control.

[0095] The principle of temperature distribution is to make the temperature of each preset temperature monitoring area close to the instantaneous temperature average, thereby reducing the non-uniformity of temperature distribution. Therefore, the minimum value of the sum of squared deviations is calculated; the smaller the deviation, the better the temperature uniformity, i.e., the objective function is:

[0096] in, It is a preset temperature monitoring area The temperature to be adjusted It is the current discrete time sequence number. The instantaneous average temperature, ,Will Substituting into the objective function, we obtain the form of a convex quadratic function:

[0097] It is a diagonal matrix (the diagonal elements are the cooling coefficients of each preset temperature monitoring zone, reflecting the sensitivity of different preset temperature monitoring zones to the exhaust flow rate of the fan). The zero-fan exhaust flow temperature for each preset temperature monitoring zone (calibrated by experimental or historical data).

[0098] The constraints of the objective function consist of two parts: one is the total exhaust flow rate constraint of the fans, and the other is the exhaust flow rate of each fan, i.e., the exhaust flow rate of the fan to be optimized in each preset temperature monitoring area. The sum equals the total exhaust flow of the fan, expressed by the formula: , ( First, there are two constraints: one is a vector of all 1s, and the other is a hardware constraint. Since each preset temperature monitoring zone is controlled by an independently adjustable exhaust valve, the exhaust flow rate of each fan to be optimized cannot exceed the valve's maximum allowable exhaust flow rate, nor can it be negative. , ( For the first The maximum allowable fan exhaust flow rate of the valve corresponding to each preset temperature monitoring zone is determined by hardware parameters.

[0099] By solving the above quadratic programming problem, the optimal solution for the exhaust flow rate of the fan to be optimized in each preset temperature monitoring area can be obtained. The virtual local flow allocation strategy in step 205a of the embodiment is based solely on static weighting of relative temperature difference, while steps 205b-207b of the embodiment, through secondary optimization, consider the dynamic response characteristics of temperature to the exhaust flow rate of the fan (such as the cooling coefficient). This allows for more precise adjustment of the fan's exhaust flow rate. This precise local allocation can significantly reduce the deviation between the temperature in each area and the instantaneous average temperature without increasing the total exhaust flow rate of the fan, further improving the uniformity of the temperature field. It is especially suitable for scenarios requiring high-precision temperature control, such as large industrial furnaces or enclosed gas collection hoods. It can effectively solve the problems of over-allocation or under-allocation that may exist in virtual local flow allocation strategies, further improving the temperature uniformity effect.

[0100] In summary, this method eliminates the need for complex heat transfer mathematical models and offers advantages such as adaptive adjustment, strong anti-interference capabilities, and high computational efficiency. It effectively improves the uniformity of temperature distribution within the enclosed gas collection hood, preventing uneven heating and ensuring the hood's lifespan. It is suitable for temperature uniformity control in various large-scale industrial heating equipment.

[0101] This invention provides an adaptive temperature uniformity control method and apparatus for a silicon carbide furnace gas collecting hood. The method involves collecting the real-time temperature of each preset temperature monitoring area within the gas collecting hood, calculating the weight of each preset temperature monitoring area based on the real-time temperature, and calculating the spatial temperature entropy based on the weight. The spatial temperature entropy is then smoothed to obtain a smoothed temperature entropy, and an adaptive rate is calculated based on the smoothed temperature entropy. The total exhaust flow rate of the fan is calculated based on the adaptive rate and the smoothed temperature entropy, and the fan exhaust flow rate allocated to each preset temperature monitoring area is calculated based on the total exhaust flow rate. The corresponding fan exhaust flow rate is used to extract tail gas carrying temperature from the corresponding air outlet for adaptive temperature uniformity control. This ensures that the real-time temperature of different preset temperature monitoring areas is uniform, preventing uneven heating of the gas collecting hood and affecting its service life. Using spatial temperature entropy as a quantitative indicator of temperature field uniformity can accurately assess temperature distribution. By dynamically adjusting the adaptive rate of the fan exhaust, a balance can be achieved between rapid response and stability, resulting in strong adaptability. Finally, under a single control output condition (i.e., a single adjustment of the fan exhaust flow rate), local optimization can be achieved through allocation without additional hardware costs.

[0102] Furthermore, as Figure 1 and Figure 2 The specific implementation of the method shown in this invention provides an adaptive temperature homogenization control device within the gas collecting hood of a silicon carbide furnace, such as... Figure 3As shown, the device includes: a data acquisition module 31, a calculation module 32, and a control module 33; The acquisition module 31 is used to acquire the real-time temperature of each preset temperature monitoring area inside the gas collection hood of the silicon carbide furnace, calculate the weight of each preset temperature monitoring area based on the real-time temperature, and calculate the spatial temperature entropy based on the weight. Calculation module 32 is used to smooth the space temperature entropy to obtain the smoothed temperature entropy, and calculate the adaptive rate based on the smoothed temperature entropy. Control module 33 is used to calculate the total exhaust flow of the fan based on the adaptive rate and the temperature entropy after smoothing, and to calculate the exhaust flow of the fan allocated to each of the preset temperature monitoring areas based on the total exhaust flow of the fan, so as to perform adaptive temperature uniformity control.

[0103] Accordingly, in order to calculate the weight of each preset temperature monitoring area based on the real-time temperature, the acquisition module 31 is specifically used to calculate the instantaneous average temperature of the current discrete time corresponding to the current discrete time ordinal number based on the real-time temperature, wherein the current discrete time is obtained by multiplying the current discrete time ordinal number by the sampling period; calculate the real-time temperature of each preset temperature monitoring area of ​​the current discrete time ordinal number by subtracting the instantaneous average temperature to obtain a temperature difference value; calculate the temperature difference value divided by the instantaneous average temperature to obtain the relative temperature difference of each preset temperature monitoring area of ​​the current discrete time ordinal number; and calculate the weight of each preset temperature monitoring area of ​​the current discrete time ordinal number based on the relative temperature difference.

[0104] Accordingly, in order to calculate the spatial temperature entropy based on the weights, the acquisition module 31 is specifically used to calculate the logarithm of each weight; calculate the product of the logarithm of the same preset temperature monitoring area and the weight to obtain the first product value of each preset temperature monitoring area; calculate the first sum of all the first product values, and determine the negative of the first sum as the spatial temperature entropy of the current discrete time sequence.

[0105] Accordingly, in order to smooth the spatial temperature entropy and obtain the smoothed temperature entropy, the calculation module 32 is specifically used to calculate the initial spatial temperature entropy at the initial discrete time, and determine the initial spatial temperature entropy as the smoothed initial spatial temperature entropy; calculate the previous smoothed spatial temperature entropy of the previous discrete time ordinal number based on the smoothed initial spatial temperature entropy; calculate the second product value of the spatial temperature entropy and the smoothing coefficient, add the previous smoothed spatial temperature entropy to the second product value to obtain the second sum, calculate the third product value of the previous smoothed spatial temperature entropy and the smoothing coefficient, and subtract the third product value from the second sum to obtain the smoothed temperature entropy of the current discrete time ordinal number.

[0106] Accordingly, in order to calculate the adaptive rate based on the smoothed temperature entropy, the calculation module 32 is specifically used to calculate the entropy change rate of the current discrete time sequence based on the previous smoothed spatial temperature entropy, the smoothed temperature entropy of the current discrete time sequence, and the sampling period; and to calculate the adaptive rate based on the absolute value of the entropy change rate, the attenuation coefficient, and the basic adaptive rate.

[0107] Accordingly, in order to calculate the total exhaust flow of the fan based on the adaptive rate and the smoothed temperature entropy, the control module 33 is specifically used to calculate the first difference between the uniformity dead zone threshold and the smoothed temperature entropy of the current discrete time sequence, and to calculate the sign function value of the first difference. Calculate the product of the symbol function value, the adaptive rate, and the single-step exhaust flow increment to obtain the fourth product value. Calculate the total exhaust flow of the previous fan at the previous discrete time sequence number. Add the total exhaust flow of the previous fan to the fourth product value to obtain the total exhaust flow of the fan at the current discrete time sequence number.

[0108] Accordingly, in order to calculate the fan exhaust flow rate allocated to each preset temperature monitoring area based on the total fan exhaust flow rate, the control module 33 is specifically used to determine whether the relative temperature difference of the preset temperature monitoring area at the current discrete time sequence is greater than 0. If it is, the relative temperature difference is determined as the corresponding positive relative temperature difference; if not, 0 is determined as the corresponding positive relative temperature difference. A positive weight is calculated based on the positive relative temperature difference. The fan exhaust flow rate of the corresponding preset temperature monitoring area is obtained by multiplying the positive weight of each preset temperature monitoring area by the total fan exhaust flow rate.

[0109] Accordingly, in order to calculate the fan exhaust flow rate allocated to each preset temperature monitoring area based on the total fan exhaust flow rate, the control module 33 specifically includes: a setting unit 331, a first determining unit 332, and a second determining unit 333; The setting unit 331 is specifically used to set the exhaust flow rate of the fan to be optimized in the preset temperature monitoring area as a variable, and to calculate the temperature to be adjusted for each preset temperature monitoring area with the current discrete time sequence based on the exhaust flow rate of the fan to be optimized. The first determining unit 332 is specifically used to obtain the instantaneous average temperature, calculate the sum of squares of the deviations between the temperature to be adjusted and the instantaneous average temperature, and determine the minimum value of the sum of squares of the deviations as the objective function; The second determining unit 333 is specifically used to determine the fan exhaust flow rate of the preset temperature monitoring area according to the objective function under the constraint that the exhaust flow rate of the fan to be optimized in each preset temperature monitoring area is non-negative and the sum of the exhaust flow rates of all the fans to be optimized is equal to the total exhaust flow rate of the fans, wherein the fan exhaust flow rate is the optimal solution of the exhaust flow rate of the fans to be optimized.

[0110] Accordingly, in order to calculate the temperature to be adjusted for each of the preset temperature monitoring areas at the current discrete time sequence based on the exhaust flow rate of the fan to be optimized, the setting unit 331 is specifically used to determine the cooling coefficient of each of the preset temperature monitoring areas; calculate the product of the exhaust flow rate of the fan to be optimized and the cooling coefficient to obtain a fifth product value; obtain the zero fan exhaust flow temperature of each of the preset temperature monitoring areas when the exhaust flow rate of the fan to be optimized is 0; calculate the zero fan exhaust flow temperature of the same preset temperature monitoring area minus the fifth product value to obtain a second difference value; and determine the second difference value as the temperature to be adjusted for each of the preset temperature monitoring areas at the current discrete time sequence.

[0111] It should be noted that for other corresponding descriptions of the functional units involved in the adaptive temperature homogenization control device inside the gas collecting hood of the silicon carbide furnace provided in this embodiment, please refer to... Figures 1 to 2 The corresponding description will not be repeated here.

[0112] Based on the above, Figures 1 to 2 Accordingly, this embodiment also provides a storage medium, which may be volatile or non-volatile, storing a computer program that, when executed by a processor, implements the above-described method. Figures 1 to 2 This paper presents an adaptive temperature homogenization control method for the gas collecting hood of a silicon carbide furnace.

[0113] Based on this understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, portable hard drive, etc.) and includes several methods for enabling a computer device (such as a personal computer, server, or network device, etc.) to execute various implementation scenarios of the present invention.

[0114] Based on the above, Figures 1 to 2 The method shown and Figure 3 , Figure 4 To achieve the above objectives, the present application also provides a computer device, specifically a personal computer, server, network device, etc., as shown in the illustrated embodiment. This computer device includes a storage medium and a processor; the storage medium stores a computer program; the processor executes the computer program to achieve the above-described objectives. Figure 1 and Figure 2 This paper presents an adaptive temperature homogenization control method for the gas collecting hood of a silicon carbide furnace.

[0115] Optionally, the computer device may also include a user interface, a network interface, a camera, radio frequency (RF) circuitry, sensors, audio circuitry, a Wi-Fi module, etc. The user interface may include a display screen, input units such as a keyboard, etc., and optional user interfaces may also include USB interfaces, card reader interfaces, etc. The network interface may optionally include standard wired interfaces, wireless interfaces (such as Wi-Fi interfaces), etc.

[0116] Those skilled in the art will understand that the computer device structure provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or combine certain components, or have different component arrangements.

[0117] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the aforementioned computer device, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the non-volatile storage medium, as well as communication with other hardware and software in the information processing entity device.

[0118] Through the above description of the embodiments, those skilled in the art can clearly understand that the present invention can be implemented by means of software plus necessary general-purpose hardware platform, or it can be implemented by hardware.

[0119] This invention provides an adaptive temperature uniformity control method and apparatus for a silicon carbide furnace gas collecting hood. The method involves collecting the real-time temperature of each preset temperature monitoring area within the gas collecting hood, calculating the weight of each preset temperature monitoring area based on the real-time temperature, and calculating the spatial temperature entropy based on the weight. The spatial temperature entropy is then smoothed to obtain a smoothed temperature entropy, and an adaptive rate is calculated based on the smoothed temperature entropy. The total exhaust flow rate of the fan is calculated based on the adaptive rate and the smoothed temperature entropy, and the fan exhaust flow rate allocated to each preset temperature monitoring area is calculated based on the total exhaust flow rate. The corresponding fan exhaust flow rate is used to extract tail gas carrying temperature from the corresponding air outlet for adaptive temperature uniformity control. This ensures that the real-time temperature of different preset temperature monitoring areas is uniform, preventing uneven heating of the gas collecting hood and affecting its service life. Using spatial temperature entropy as a quantitative indicator of temperature field uniformity can accurately assess temperature distribution. By dynamically adjusting the adaptive rate of the fan exhaust, a balance can be achieved between rapid response and stability, resulting in strong adaptability. Finally, under a single control output condition (i.e., a single adjustment of the fan exhaust flow rate), local optimization can be achieved through allocation without additional hardware costs.

[0120] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing the present invention. Those skilled in the art will understand that the modules in the apparatus of the embodiment can be distributed within the apparatus of the embodiment as described, or can be located in one or more apparatuses different from this embodiment, with corresponding changes. The modules of the above-described embodiment can be combined into one module, or further divided into multiple sub-modules. The above-described serial numbers are for descriptive purposes only and do not represent the superiority or inferiority of the embodiment. The above disclosures are only a few specific embodiments of the present invention; however, the present invention is not limited thereto, and any variations conceived by those skilled in the art should fall within the protection scope of the present invention.

Claims

1. A method for adaptive temperature homogenization control within the gas collecting hood of a silicon carbide furnace, characterized in that, The method includes: Real-time temperature of each preset temperature monitoring area inside the gas collection hood of the silicon carbide furnace is collected; weight of each preset temperature monitoring area is calculated based on the real-time temperature; spatial temperature entropy is calculated based on the weight. The space temperature entropy is smoothed to obtain the smoothed temperature entropy, and the adaptive rate is calculated based on the smoothed temperature entropy. The total exhaust flow rate of the fan is calculated based on the adaptive rate and the temperature entropy after smoothing. The exhaust flow rate of the fan allocated to each of the preset temperature monitoring areas is then calculated based on the total exhaust flow rate of the fan to perform adaptive temperature uniformity control.

2. The adaptive temperature uniformity control method within the gas collecting hood of a silicon carbide furnace according to claim 1, characterized in that, The step of calculating the weight of each preset temperature monitoring zone based on the real-time temperature includes: The instantaneous average temperature is calculated based on the real-time temperature and the current discrete time ordinal number corresponding to the current discrete time. The current discrete time is obtained by multiplying the current discrete time ordinal number corresponding to the current discrete time by the sampling period. The real-time temperature of each preset temperature monitoring area at the current discrete time sequence is subtracted from the average instantaneous temperature to obtain a temperature difference. The temperature difference is then divided by the average instantaneous temperature to obtain the relative temperature difference of each preset temperature monitoring area at the current discrete time sequence. The weight of each preset temperature monitoring region is calculated based on the relative temperature difference for the current discrete time sequence.

3. The adaptive temperature uniformity control method within the gas collecting hood of a silicon carbide furnace according to claim 2, characterized in that, The calculation of spatial temperature entropy based on the weights includes: Calculate the logarithm of each of the weights; Calculate the product of the logarithm and the weight for the same preset temperature monitoring area to obtain the first product value for each preset temperature monitoring area; Calculate the first sum of all the first product values, and determine the spatial temperature entropy of the current discrete time sequence number by taking the negative of the first sum.

4. The adaptive temperature uniformity control method within the gas collecting hood of a silicon carbide furnace according to claim 2, characterized in that, The smoothing process of the spatial temperature entropy to obtain the smoothed temperature entropy includes: Calculate the initial spatial temperature entropy at the initial discrete time, and determine the initial spatial temperature entropy as the initial spatial temperature entropy after smoothing. Calculate the previous smoothed spatial temperature entropy of the previous discrete time sequence number based on the initial spatial temperature entropy after smoothing. Calculate the second product of the spatial temperature entropy and the smoothing coefficient, add the spatial temperature entropy after the previous smoothing process to the second product to obtain the second sum, calculate the third product of the spatial temperature entropy after the previous smoothing process and the smoothing coefficient, and subtract the third product from the second sum to obtain the smoothed temperature entropy of the current discrete time sequence.

5. The adaptive temperature uniformity control method within the gas collecting hood of a silicon carbide furnace according to claim 4, characterized in that, The step of calculating the adaptive rate based on the smoothed temperature entropy includes: The entropy change rate of the current discrete time sequence is calculated based on the spatial temperature entropy after the previous smoothing process, the temperature entropy after the smoothing process of the current discrete time sequence, and the sampling period. The adaptive rate is calculated based on the absolute value of the entropy change rate, the decay coefficient, and the basic adaptive rate.

6. The adaptive temperature uniformity control method within the gas collecting hood of a silicon carbide furnace according to claim 5, characterized in that, The step of calculating the total exhaust flow rate of the fan based on the adaptive rate and the smoothed temperature entropy includes: Calculate the first difference between the uniformity dead zone threshold and the smoothed temperature entropy after subtracting the current discrete time sequence number, and calculate the sign function value of the first difference; Calculate the product of the symbol function value, the adaptive rate, and the single-step exhaust flow increment to obtain the fourth product value. Calculate the total exhaust flow of the previous fan at the previous discrete time sequence number. Add the total exhaust flow of the previous fan to the fourth product value to obtain the total exhaust flow of the fan at the current discrete time sequence number.

7. The adaptive temperature uniformity control method within the gas collecting hood of a silicon carbide furnace according to claim 2, characterized in that, The step of calculating the fan exhaust flow rate allocated to each of the preset temperature monitoring zones based on the total fan exhaust flow rate includes: Determine whether the relative temperature difference of the preset temperature monitoring area at the current discrete time sequence is greater than 0. If it is, then the relative temperature difference is determined as the corresponding positive relative temperature difference. If not, then 0 is determined as the corresponding positive relative temperature difference. Calculate the positive weight based on the positive relative temperature difference. The fan exhaust flow rate of the corresponding preset temperature monitoring area is obtained by multiplying the positive weight of each preset temperature monitoring area by the total exhaust flow rate of the fan.

8. The adaptive temperature uniformity control method within the gas collecting hood of a silicon carbide furnace according to claim 2, characterized in that, The step of calculating the fan exhaust flow rate allocated to each of the preset temperature monitoring zones based on the total fan exhaust flow rate includes: The exhaust flow rate of the fan to be optimized in the preset temperature monitoring area is set as a variable, and the temperature to be adjusted in each preset temperature monitoring area with the current discrete time sequence is calculated based on the exhaust flow rate of the fan to be optimized. Obtain the instantaneous average temperature, calculate the sum of squares of the deviations between the temperature to be adjusted and the instantaneous average temperature, and determine the minimum value of the sum of squares of deviations as the objective function; Under the constraint that the exhaust flow rate of the fan to be optimized in each preset temperature monitoring area is non-negative and the sum of the exhaust flow rates of all the fans to be optimized is equal to the total exhaust flow rate of the fans, the exhaust flow rate of the fans in the preset temperature monitoring area is determined according to the objective function, wherein the exhaust flow rate of the fans is the optimal solution of the exhaust flow rate of the fans to be optimized.

9. The adaptive temperature homogenization control method within the gas collecting hood of a silicon carbide furnace according to claim 8, characterized in that, The step of calculating the temperature to be adjusted for each preset temperature monitoring area based on the exhaust flow rate of the fan to be optimized, using the current discrete time sequence number, includes: Determine the cooling coefficient for each of the preset temperature monitoring zones; Calculate the product of the exhaust flow rate of the fan to be optimized and the cooling coefficient to obtain the fifth product value; Obtain the zero fan exhaust flow temperature of each preset temperature monitoring area when the exhaust flow rate of the fan to be optimized is 0, calculate the zero fan exhaust flow temperature of the same preset temperature monitoring area minus the fifth product value to obtain the second difference, and determine the second difference as the temperature to be adjusted for each preset temperature monitoring area of ​​the current discrete time sequence.

10. An adaptive temperature homogenization control device for a silicon carbide furnace gas collecting hood, characterized in that, The device includes: The data acquisition module is used to acquire the real-time temperature of each preset temperature monitoring area inside the gas collection hood of the silicon carbide furnace, calculate the weight of each preset temperature monitoring area based on the real-time temperature, and calculate the spatial temperature entropy based on the weight. The calculation module is used to smooth the space temperature entropy to obtain the smoothed temperature entropy, and calculate the adaptive rate based on the smoothed temperature entropy. The control module is used to calculate the total exhaust flow of the fan based on the adaptive rate and the temperature entropy after smoothing, and to calculate the exhaust flow of the fan allocated to each of the preset temperature monitoring areas based on the total exhaust flow of the fan, so as to perform adaptive temperature uniformity control.

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