A method and system for controlling the top air circulation of an autoclave

Abstract

The present application relates to the technical field of composite curing forming equipment, and particularly relates to a hot press tank top air circulation control method and system. The present application solves the technical problem that the existing method cannot distinguish the real cause of current fluctuation, thereby failing to achieve precise control of the flow field. The method comprises: obtaining the operating state parameters of the hot press tank; determining the theoretical load characteristic value based on the gas pressure, the gas temperature and the fan speed; dynamically decoupling the mechanical loss component for overcoming mechanical friction from the aerodynamic load component for driving gas flow in the active current based on the theoretical load characteristic value and the active current to determine the aerodynamic response coefficient; determining the circulation short-circuit ratio based on the aerodynamic response coefficient and the preset reference information reflecting the health flow field characteristics; and adjusting the speed of the fan to the target speed based on the circulation short-circuit ratio using the extreme value search strategy. The present application is used in the hot press tank top air circulation control scene.

Description

Technical Field

[0001] This invention relates to the field of composite material curing and molding equipment technology, specifically to a method and system for controlling the air circulation at the top of an autoclave. Background Technology

[0002] In the fields of composite material manufacturing and plastic waste recycling, autoclaves are key curing and molding equipment, and the uniformity of their internal temperature field directly affects the molding quality of the products. To ensure uniform heating of large components or mold areas within the autoclave, existing autoclave equipment typically employs a top fan combined with a central air intake to drive heated gas in a circulating flow within the autoclave, thereby achieving heat exchange and temperature equilibrium. During actual operation of the autoclave, especially after entering the high-pressure curing stage, the gas pressure inside the autoclave increases significantly, leading to a sharp increase in gas density and fluid inertia. Under these conditions, if the top fan speed is not properly controlled, the high-speed airflow can easily bend back at the air guide hood outlet due to excessive inertia and directly enter the central negative pressure zone, forming a short-circuit loop that bypasses the mold area. This airflow short-circuit phenomenon not only deteriorates the temperature distribution on the mold surface, severely affecting the curing quality of the components, but also results in ineffective energy consumption of the fan. Existing technology typically uses monitoring the motor operating current to determine the fan's load status. However, the autoclave process is characterized by complex temperature and pressure variations. During the prolonged curing process, the viscosity of the motor bearing grease decreases with increasing temperature, causing a drift in mechanical friction resistance. Simultaneously, changes in gas density with pressure and temperature also cause fluctuations in the pneumatic load. This results in the total motor current signal being a combination of the coupled effects of mechanical friction, changes in gas properties, and alterations in the actual flow field structure. Existing control methods struggle to identify the true cause of current fluctuations, thus failing to achieve precise and effective control of the flow field. Consequently, the overall performance of the autoclave operation cannot meet increasingly stringent process requirements. Summary of the Invention

[0003] To address the technical problem that existing methods struggle to identify the true cause of current fluctuations, thus hindering precise control of the flow field and causing the overall performance of autoclaves to fail to meet increasingly stringent process requirements, this invention aims to provide a method and system for controlling the top air circulation of an autoclave. The specific technical solution adopted is as follows:

[0004] In a first aspect, the present invention provides a method for controlling the top air circulation of an autoclave. The method includes: acquiring operating state parameters of the autoclave; the operating state parameters include at least: gas pressure, gas temperature, fan speed, and active current of the motor; determining a theoretical load characterization value based on the gas pressure, gas temperature, and fan speed; the theoretical load characterization value characterizing the theoretical driving intensity applied by the fan to the gas; dynamically decoupling the mechanical loss component used to overcome mechanical friction from the aerodynamic load component used to drive gas flow based on the theoretical load characterization value and the active current, and determining an aerodynamic response coefficient; the aerodynamic response coefficient characterizing the effectiveness of the flow field structure; determining a cycle short-circuit ratio based on the aerodynamic response coefficient and preset benchmark information reflecting healthy flow field characteristics; the cycle short-circuit ratio quantifying the current flow field failure level; and adjusting the fan speed to a target speed using an extreme value search strategy based on the cycle short-circuit ratio; the target speed being the speed corresponding to when the cycle short-circuit ratio approaches its minimum value.

[0005] In conjunction with the first aspect mentioned above, in one possible implementation, the method specifically includes: determining a theoretical gas load factor based on gas pressure, gas temperature, and fan speed; the theoretical gas load factor is used to comprehensively reflect the degree of coupling influence of current gas density and speed on fan drive intensity; and the theoretical gas load factor is determined as a theoretical load characterization value.

[0006] In conjunction with the first aspect mentioned above, in one possible implementation, the method specifically includes: constructing a data sequence based on current data pairs and multiple historical data pairs; the data pairs are composed of theoretical load characterization values ​​and active current; determining the operating condition type of the autoclave at the current moment based on the fluctuation degree of the theoretical load characterization values ​​in the data sequence; and determining a decoupling method that matches the operating condition type based on the operating condition type to perform decoupling and determine the aerodynamic response coefficient.

[0007] In conjunction with the first aspect mentioned above, in one possible implementation, the method specifically includes: when the operating condition type is dynamic, performing linear regression analysis on multiple data pairs in the data sequence, and determining the slope of the linear regression line as the aerodynamic response coefficient; the dynamic operating condition is the operating condition in which the fluctuation of the theoretical load characterization value in the data sequence meets the data conditions for performing regression analysis; when the operating condition type is steady-state, obtaining a preset mechanical loss base value, performing temperature compensation correction on the mechanical loss base value based on the current gas temperature, and determining the corrected mechanical loss base value; the steady-state operating condition is the operating condition in which the fluctuation of the theoretical load characterization value in the data sequence is insufficient to support effective regression analysis; and determining the aerodynamic response coefficient based on the current active current, the theoretical load characterization value, and the corrected mechanical loss base value.

[0008] In conjunction with the first aspect mentioned above, in one possible implementation, the method specifically includes: determining that the flow field is in a healthy state when the gas pressure is lower than a preset safe pressure threshold; and storing the aerodynamic response coefficient corresponding to the gas temperature as a reference response coefficient in a health benchmark library, using the gas temperature as an index.

[0009] In conjunction with the first aspect mentioned above, in one possible implementation, the method specifically includes: determining a corresponding reference response coefficient from a health benchmark library based on the gas temperature at the current moment; determining a pressure correction factor to compensate for the difference in fluid characteristics between the high-pressure condition and the low-pressure benchmark based on the gas pressure at the current moment; and determining the cycle short-circuit ratio based on the aerodynamic response coefficient, the reference response coefficient, and the pressure correction factor.

[0010] In conjunction with the first aspect mentioned above, in one possible implementation, the method specifically includes: obtaining a preset pressure compensation coefficient; and determining a pressure correction factor based on the pressure difference between the current gas pressure and a preset safe pressure threshold, as well as the pressure compensation coefficient.

[0011] In conjunction with the first aspect mentioned above, in one possible implementation, the method specifically includes: determining the pressure-corrected reference response coefficient based on the reference response coefficient and the pressure correction factor; and determining the cyclic short-circuit ratio based on the aerodynamic response coefficient and the corrected reference response coefficient.

[0012] In conjunction with the first aspect mentioned above, in one possible implementation, the method specifically includes: obtaining a preset mechanical resistance temperature coefficient; compensating the mechanical loss base value based on the temperature difference between the current gas temperature and the reference temperature corresponding to the mechanical loss base value, and the mechanical resistance temperature coefficient, to determine the corrected mechanical loss base value.

[0013] Secondly, the present invention provides a top air circulation control system for an autoclave, used to implement the top air circulation control method for an autoclave as described in the first aspect above; the system includes: a data acquisition module for acquiring the operating status parameters of the autoclave; the operating status parameters include at least: gas pressure, gas temperature, fan speed, and active current of the motor; a theoretical load determination module for determining a theoretical load characterization value based on the gas pressure, gas temperature, and fan speed; the theoretical load characterization value characterizes the theoretical driving intensity applied by the fan to the gas; and a parameter decoupling module for determining the theoretical load characterization value and active current based on the theoretical load characterization value and the active current. The flow field is dynamically decoupled from the mechanical loss component used to overcome mechanical friction in the active current to determine the aerodynamic load component used to drive the gas flow, thus determining the aerodynamic response coefficient. The aerodynamic response coefficient is used to characterize the effectiveness of the flow field structure. The state quantification module is used to determine the cyclic short-circuit ratio based on the aerodynamic response coefficient and preset benchmark information reflecting the characteristics of a healthy flow field. The cyclic short-circuit ratio is used to quantify the current degree of flow field failure. The control adjustment module is used to adjust the fan speed to the target speed based on the cyclic short-circuit ratio using an extreme value search strategy. The target speed is the speed corresponding to when the cyclic short-circuit ratio tends to the minimum value.

[0014] The present invention has the following beneficial effects:

[0015] This invention acquires multi-dimensional operating parameters such as gas pressure, gas temperature, fan speed, and motor active current during the operation of an autoclave. First, it constructs a theoretical load characterization value based on gas pressure, gas temperature, and fan speed to represent the theoretical driving strength of the fan. Then, it dynamically decouples the mechanical friction component and aerodynamic load component in the current signal, which are originally difficult to separate, by combining the active current, and obtains an aerodynamic response coefficient that can purely reflect the effectiveness of the flow field structure. Based on this aerodynamic response coefficient and preset healthy flow field benchmark information, it calculates the cyclic short-circuit ratio to quantify the degree of flow field failure. Finally, it uses an extreme value search strategy to automatically adjust the fan speed to the target speed that minimizes the cyclic short-circuit ratio. This method fundamentally solves the technical challenge of accurately identifying the flow field state due to the coupling of mechanical friction drift and aerodynamic load changes in traditional control. By decoupling the mixed current signal into independent physical components, it achieves precise quantification of the airflow short-circuit degree and adaptive optimization of the optimal speed point through extreme value search. This significantly improves the uniformity of the temperature field inside the autoclave without relying on complex fluid dynamics models, effectively avoiding energy waste in the blower under ineffective short-circuit conditions, and achieving a dual optimization of process quality and operational efficiency. It also solves the technical problem that existing methods struggle to identify the true cause of current fluctuations, thus failing to achieve precise control of the flow field effectiveness and causing the overall performance of the autoclave to fail to meet increasingly stringent process requirements. Attached Figure Description

[0016] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A schematic flowchart illustrating a method for controlling air circulation at the top of an autoclave, provided in one embodiment of the present invention;

[0018] Figure 2 This is a schematic diagram of the system architecture of a top air circulation control system for an autoclave, provided as an embodiment of the present invention. Detailed Implementation

[0019] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a method and system for controlling the top air circulation of an autoclave according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0021] The following description, in conjunction with the accompanying drawings, details the specific scheme of the air circulation control method and system for the top of an autoclave provided by the present invention.

[0022] Please see Figure 1 The diagram illustrates a flow chart of a method for controlling the top air circulation of an autoclave according to an embodiment of the present invention. The method includes the following steps S101-S105, which will be described in detail below.

[0023] S101. Obtain the operating status parameters of the autoclave.

[0024] The operating parameters include at least: gas pressure, gas temperature, fan speed, and motor active current.

[0025] In one possible implementation, a data acquisition command is triggered via a fieldbus to read the current operating status parameters in real time from sensors and frequency converters deployed in various parts of the autoclave.

[0026] For example, the gas pressure is obtained by reading the signal from a pressure transmitter installed on the tank, and is denoted as gas pressure. The unit is Pascal (Pa), used to characterize the degree of compression of the gas inside the tank. The gas temperature is obtained by arithmetic averaging of the signals from multiple thermocouples placed at the inlet and outlet of the air guide shroud and converting it into thermodynamic temperature, denoted as gas temperature. The unit is Kelvin (K), used to characterize the thermodynamic state of a gas. The fan speed is obtained by reading the real-time operating frequency fed back from the fan's frequency converter driver, converting it into mechanical angular velocity based on the number of motor pole pairs, and denoted as fan speed. The unit is radians per second (rad / s), used to characterize the angular velocity of the impeller rotation. The active current of the motor is obtained by reading the torque current component output by the vector control unit of the frequency converter driver, and is denoted as active current. The unit is ampere (A), which is used to characterize the total energy consumed by an electric motor to overcome aerodynamic loads and mechanical friction.

[0027] S102. Determine the theoretical load characterization value based on gas pressure, gas temperature, and fan speed.

[0028] Among them, the theoretical load characterization value is used to characterize the theoretical driving intensity applied by the fan to the gas.

[0029] In one possible implementation, after obtaining the set of operating state parameters after cleaning, a theoretical load characterization value is calculated based on the current gas pressure, gas temperature, and fan speed to characterize the theoretical driving intensity applied by the fan to the gas.

[0030] For example, since the gas density inside the autoclave varies significantly with pressure and temperature, and the fan load is proportional to the square of the gas density and rotational speed, it is necessary to integrate multidimensional environmental variables into a comprehensive index that can uniformly characterize the theoretical driving strength of the fan. Based on the gas compressibility represented by the current gas pressure, the thermal motion state of gas molecules represented by the gas temperature, and the impeller rotational angular velocity represented by the fan speed, a theoretical load characterization value is constructed. This theoretical load characterization value comprehensively reflects the coupled influence of the current gas density and rotational speed on the fan driving strength. A higher value indicates that the fan is theoretically under heavy load (e.g., high pressure, high speed); a lower value indicates that the fan is under light load (e.g., low pressure, low speed). This characterization value serves as a benchmark for subsequently decoupling the active current into mechanical loss components and aerodynamic load components, providing a unified quantitative scale for accurately identifying the effectiveness of the flow field structure.

[0031] S103. Based on the theoretical load characterization value and active current, the mechanical loss component used to overcome mechanical friction in the active current is dynamically decoupled from the aerodynamic load component used to drive gas flow, and the aerodynamic response coefficient is determined.

[0032] Among them, the aerodynamic response coefficient is used to characterize the effectiveness of the flow field structure.

[0033] In one possible implementation, after obtaining the theoretical load characterization value at the current moment, the mechanical friction component and aerodynamic work component mixed in the total motor current are separated by combining the collected active current, so as to extract the aerodynamic response coefficient that can purely reflect the effectiveness of the flow field structure.

[0034] For example, since the total active current output by the motor is composed of the aerodynamic load component driving the gas flow and the mechanical loss component overcoming mechanical resistance, directly monitoring the total current cannot distinguish whether the change in the flow field state is caused by airflow short-circuiting or mechanical friction drift. Therefore, utilizing the physical characteristics that aerodynamic load is positively correlated with the theoretical load characterization value, while mechanical friction is relatively constant in a short time, the two are decoupled through statistical methods. Specifically, the theoretical load characterization value is used as the independent variable, and the active current as the dependent variable, to construct a mapping relationship between the two. By analyzing the current response amplitude caused by a unit change in the theoretical load characterization value, the aerodynamic response coefficient is obtained. This coefficient characterizes the increase in motor current when the theoretical load characterization value increases by one unit. Its value directly reflects the efficiency of the fan impeller in doing work on the airflow. The larger the coefficient, the stronger the current response under the same theoretical load, i.e., the stronger the reaction force of the airflow on the impeller, and the more effective the flow field structure; the smaller the coefficient, the lower the airflow efficiency, and the possible existence of airflow short-circuiting or poor flow.

[0035] S104. Based on the aerodynamic response coefficient and preset benchmark information reflecting the characteristics of a healthy flow field, determine the cyclic short-circuit ratio.

[0036] The cyclic short-circuit ratio is used to quantify the degree of failure of the current flow field.

[0037] In one possible implementation, after obtaining the aerodynamic response coefficient at the current moment, the cyclic short-circuit ratio is calculated by combining it with pre-established benchmark information that reflects the characteristics of a healthy flow field, in order to quantify the degree of failure of the current flow field.

[0038] For example, due to the extreme range of gas temperature and pressure within the autoclave, physical properties such as gas viscosity change significantly, leading to non-fault-related physical drift in the aerodynamic response coefficient. Therefore, the health of the flow field cannot be determined directly based on the absolute value of the aerodynamic response coefficient; instead, it needs to be compared with a benchmark value that reflects the expected level of a healthy flow field under current operating conditions. To this end, a health benchmark library indexed by gas temperature is pre-established, storing reference response coefficients corresponding to healthy flow fields at different temperatures. After obtaining the current aerodynamic response coefficient, the corresponding reference response coefficient is obtained from this benchmark library based on the current gas temperature, serving as the expected aerodynamic response level for a healthy flow field at the current temperature. Simultaneously, considering the physical differences between fluid characteristics (such as Reynolds number) under high-pressure conditions and low-pressure benchmark conditions, the benchmark value is adaptively corrected based on the current gas pressure to eliminate the influence of cross-flow state physical characteristic differences on the results. Finally, the current aerodynamic response coefficient is compared with the pressure-corrected benchmark value to calculate a cycle short-circuit ratio between 0 and 1. This ratio quantifies the degree to which the current flow field deviates from a healthy state. When the ratio approaches 0, it indicates that the actual aerodynamic response is close to the healthy baseline, the flow field structure is effective, and the airflow can fully penetrate the mold area for circulating heat exchange. When the ratio approaches 1, it indicates that the actual aerodynamic response is far below the healthy baseline, the flow field has a serious airflow short-circuit phenomenon, and the gas does not flow effectively through the mold area and returns directly to the fan intake.

[0039] S105. Based on the cyclic short-circuit ratio, an extreme value search strategy is used to adjust the fan speed to the target speed.

[0040] The target speed is the speed at which the cyclic short-circuit ratio approaches its minimum value.

[0041] In one possible implementation, after obtaining the current cyclic short-circuit ratio, the controller uses it as a feedback variable for closed-loop control and employs an extreme value search strategy to dynamically adjust the fan speed so that the cyclic short-circuit ratio tends to the optimal speed point corresponding to the minimum value.

[0042] For example, considering the complexity of the physical causes of airflow short-circuiting under high-pressure conditions—which can be due to boundary layer separation caused by excessively high flow velocity, or insufficient momentum due to excessively low flow velocity preventing penetration of the mold region—simple deceleration or acceleration logic lacks universality. Therefore, this embodiment abandons the traditional approach of pre-setting a fixed control direction and adopts an extreme value search strategy for optimization. First, a flow field efficiency index is defined based on the cyclic short-circuit ratio. This efficiency index is negatively correlated with the cyclic short-circuit ratio; that is, the smaller the cyclic short-circuit ratio, the larger the efficiency index, indicating a better flow field circulation state. Subsequently, using the current rotational speed as a base point, a small step-size rotational speed perturbation is applied to the fan, and the trend of the efficiency index after the perturbation is observed. If the efficiency index improves after the perturbation, it indicates that the current perturbation direction is correct, and the exploration continues in this direction; if the efficiency index deteriorates after the perturbation, it indicates that the current perturbation direction is incorrect, and the perturbation direction is reversed. By continuously adjusting the fan speed, the drive system gradually approaches the operating point where the efficiency index reaches its maximum value. The corresponding cycle short-circuit ratio at this operating point tends to the minimum value, which is the target speed with the best airflow penetration under the current operating condition.

[0043] The technical solution provided by the above embodiments can bring at least the following beneficial effects: This embodiment obtains multi-dimensional operating state parameters such as gas pressure, gas temperature, fan speed and motor active current during the operation of the autoclave. First, it constructs a theoretical load characterization value based on gas pressure, gas temperature and fan speed to characterize the theoretical driving strength of the fan. Then, it combines the active current to dynamically decouple the mechanical friction component and the aerodynamic load component in the current signal, which were originally difficult to separate, to obtain an aerodynamic response coefficient that can purely reflect the effectiveness of the flow field structure. Then, based on the aerodynamic response coefficient and the preset healthy flow field benchmark information, it calculates the cyclic short-circuit ratio to quantify the degree of flow field failure. Finally, it adopts an extreme value search strategy to automatically adjust the fan speed to the target speed that makes the cyclic short-circuit ratio tend to the minimum value. This method fundamentally solves the technical challenge of accurately identifying the flow field state due to the coupling of mechanical friction drift and aerodynamic load changes in traditional control. By decoupling the mixed current signal into independent physical components, it achieves precise quantification of the airflow short-circuit degree and adaptive optimization of the optimal speed point through extreme value search. This significantly improves the uniformity of the temperature field inside the autoclave without relying on complex fluid dynamics models, effectively avoiding energy waste in the blower under ineffective short-circuit conditions, and achieving a dual optimization of process quality and operational efficiency. It also solves the technical problem that existing methods struggle to identify the true cause of current fluctuations, thus failing to achieve precise control of the flow field effectiveness and causing the overall performance of the autoclave to fail to meet increasingly stringent process requirements.

[0044] In one possible implementation, the process of determining the theoretical load characterization value based on gas pressure, gas temperature, and fan speed can be specifically implemented through the following S201-S202, which will be explained in detail below.

[0045] S201. Determine the theoretical gas load factor based on gas pressure, gas temperature, and fan speed.

[0046] Among them, the theoretical gas load factor is used to comprehensively reflect the degree of coupling influence between the current gas density and rotational speed on the drive strength of the fan.

[0047] In one possible implementation, after obtaining the gas pressure, gas temperature, and fan speed at the current moment, a theoretical gas load factor is calculated based on the fan similarity law and the ideal gas equation of state. This theoretical load factor is used to comprehensively reflect the degree of coupling influence of the current gas density and speed on the fan drive strength.

[0048] For example, the theoretical gas loading factor satisfies the following formula 1:

[0049] Formula 1

[0050] in, Let k be the gas pressure at time k, expressed in Pascals (Pa). This pressure characterizes the intensity of collisions between gas molecules and the container wall, reflecting the degree of gas compression. Let K be the gas temperature at time k, expressed in Kelvin (K), which characterizes the intensity of the thermal motion of gas molecules. Let be the fan speed at time k, expressed in radians per second (rad / s), representing the angular velocity of the fan impeller. The term represents the gas density at the current moment. According to the ideal gas law, gas density is directly proportional to pressure and inversely proportional to temperature. The higher the pressure or the lower the temperature, the greater the gas density. The term characterizes the nonlinear effect of rotational speed on load. According to the fan similarity law, the driving force exerted by the fan on the gas is proportional to the square of the rotational speed. Multiplying the two parts yields the theoretical gas load factor, which reflects the theoretical driving intensity that should be applied to the fluid when the fan rotates at the current speed under the current gas density environment. Gas pressure is positively correlated with the theoretical gas load factor, gas temperature is negatively correlated with the theoretical gas load factor, and fan speed is positively correlated with the theoretical gas load factor.

[0051] It is understandable that the gas temperature in the autoclave will fluctuate during actual operation. It remains within the positive temperature range set by the process (far above absolute zero), therefore the denominator in the formula... The value is always positive, eliminating the risk of division by zero. To further ensure the robustness of the control system, data validity verification logic is implemented in the temperature acquisition stage. If the detected temperature value exceeds the preset valid range, it is determined to be a sensor malfunction. Preset the process temperature according to the commonly used process temperature of the autoclave (e.g., 373K).

[0052] S202. The theoretical gas loading factor is determined as the theoretical load characterization value.

[0053] In one possible implementation, after calculating the theoretical gas load factor at the current moment, the theoretical gas load factor is directly used as the theoretical load characterization value required for the subsequent dynamic decoupling step, so as to separate the mechanical loss component in the active current used to overcome mechanical friction from the aerodynamic load component used to drive gas flow.

[0054] Understandably, the theoretical gas load factor is a comprehensive index obtained by physically integrating gas pressure, gas temperature, and fan speed. Its value fully encompasses the coupled influence of gas density and speed on fan drive strength under the current operating conditions. Therefore, the theoretical gas load factor calculated at the current moment is assigned to the theoretical load characterization value as an input variable for subsequent regression analysis or back-calculation. This assignment operation establishes a mapping relationship from the original environmental parameters to standardized independent variables, making the theoretical load characterization value a bridge connecting multidimensional physical quantities and subsequent decoupling algorithms. On the one hand, it inherits the comprehensive characterization capability of gas density and speed from the theoretical gas load factor; on the other hand, as a unified input interface, it provides a standardized data format for selecting appropriate decoupling methods under different operating conditions.

[0055] The technical solution provided in the above embodiments can bring at least the following beneficial effects: This embodiment uses the theoretical gas load factor, which is jointly determined by gas pressure, gas temperature, and fan speed, as a specific implementation method for the theoretical load characterization value. This theoretical gas load factor comprehensively reflects the degree of coupling influence of current gas density and fan speed on drive strength. It fully considers the physical characteristics of gas density changing with pressure and temperature under high-pressure conditions in autoclaves, transforming multi-dimensional environmental parameters into unified quantitative indicators. This provides a benchmark for independent variables that highly matches physical reality for subsequent current decoupling, making the calculation of aerodynamic response coefficients more accurate and reliable, and further improving the adaptability and accuracy of the entire control method under variable temperature and pressure environments.

[0056] In one possible implementation, the process of dynamically decoupling the mechanical loss component used to overcome mechanical friction and the aerodynamic load component used to drive gas flow in the active current based on the theoretical load characterization value and the active current, and determining the aerodynamic response coefficient, can be specifically implemented through the following S301-S303, which will be described in detail below.

[0057] S301. Construct a data sequence based on the current time data pair and multiple historical time data pairs.

[0058] The data pairs are composed of theoretical load characterization values ​​and active current.

[0059] In one possible implementation, after obtaining the theoretical load characterization value and active current at the current moment, the two are combined into a data pair for the current moment, and then combined with multiple previously stored historical time data pairs to construct a data sequence for subsequent analysis.

[0060] For example, a fixed-length first-in-first-out queue is maintained to store data pairs from the most recent control cycles. In each control cycle, the theoretical load representation value at the current moment is first recorded as... The active current at the current moment is denoted as And combine the two into a data pair for the current time. Subsequently, the current data pair is pushed to the end of the queue, while the oldest historical data pair at the very front of the queue is removed, thus maintaining the queue length at a preset fixed value m (for example, m is 50). After this operation, the queue forms a data sequence containing the current data pair and the most recent m-1 historical data pairs. Each data pair in this sequence consists of the theoretical load characterization value and active current at the same moment, ensuring a strict correspondence between the independent and dependent variables over time. The theoretical load characterization value serves as the independent variable, representing the theoretical driving intensity of the fan on the gas at each moment; the active current serves as the dependent variable, representing the total electromagnetic torque current actually output by the motor at the corresponding moment.

[0061] S302. Based on the fluctuation of the theoretical load characterization value in the data sequence, determine the operating condition type of the autoclave at the current moment.

[0062] In one possible implementation, after constructing a data sequence containing data pairs of the current time and multiple historical time points, the fluctuation of the theoretical load characterization value in the sequence is quantitatively analyzed, and the current operating condition type of the autoclave is identified based on the analysis results.

[0063] For example, firstly, the arithmetic mean of all theoretical load characterization values ​​in the data sequence is calculated. Then, based on this mean, the sum of squared deviations of the theoretical load characterization values ​​at each time point in the sequence from the mean is calculated, and then divided by the sequence length to obtain the variance of the theoretical load characterization values. This variance is a statistical indicator that quantifies the degree of fluctuation; its magnitude directly reflects the drastic change in the theoretical load characterization values ​​within the most recent time window. A larger variance indicates more drastic fluctuations in the theoretical load characterization values, suggesting the system is in a dynamic process; a smaller variance indicates that the theoretical load characterization values ​​are more stable, suggesting the system is in a relatively stable operating state.

[0064] The calculated variance is compared with a preset fluctuation threshold. This fluctuation threshold is a pre-calibrated constant (exemplary, 1.0) used to distinguish the boundary between dynamic and steady-state operating conditions. If the variance is greater than the threshold, it indicates that the fluctuation of the theoretical load characterization value in the data sequence is sufficiently significant, and the data points have a sufficient span in the independent variable dimension, satisfying the data conditions for regression analysis. In this case, the autoclave is determined to be in a dynamic operating condition. Dynamic operating conditions typically correspond to stages where the system state changes, such as when the fan speed is being adjusted or the pressure is rising or falling. If the variance is less than or equal to the threshold, it indicates that the fluctuation of the theoretical load characterization value is small, and the data points are too clustered to support effective regression analysis. In this case, the autoclave is determined to be in a steady-state operating condition. Steady-state operating conditions typically correspond to stages where the system state changes slowly, such as when the speed is constant and the pressure is maintained, and the temperature and pressure remain stable.

[0065] S303. Based on the operating condition type, determine the decoupling method that matches the operating condition type and perform decoupling to determine the aerodynamic response coefficient.

[0066] In one possible implementation, after identifying the current operating condition type of the autoclave, a pre-configured corresponding decoupling method is selected according to the operating condition type, and the mapping relationship between the theoretical load characterization value and the active current is analyzed, thereby determining the aerodynamic response coefficient that can purely reflect the effectiveness of the flow field structure.

[0067] For example, due to the fundamental differences in the statistical characteristics of data sequences under dynamic and steady-state operating conditions, two different decoupling logics are employed to adapt to these two conditions. Under dynamic conditions, the theoretical load characteristics in the data sequence fluctuate significantly, and the data points are dispersed across the independent variable dimension, providing a statistical basis for regression analysis. In this case, a linear regression-based decoupling method is used to directly fit multiple data pairs in the data sequence and extract the aerodynamic response coefficients from the regression results. This method leverages the inherent dispersion of the data to simultaneously separate the aerodynamic response coefficients and the mechanical loss baseline values, achieving simultaneous acquisition of both in a single calculation. Under steady-state conditions, the theoretical load characteristics in the data sequence fluctuate less, and the data points are too clustered to support effective regression analysis. In this case, a temperature-compensated correction-based inverse calculation decoupling method is employed. This method does not rely on data fluctuations. Instead, it uses a preset mechanical loss baseline as a known quantity, and compensates for this baseline by incorporating the current gas temperature to accommodate mechanical friction drift caused by temperature changes. Then, based on the current active current, theoretical load characterization value, and the corrected mechanical loss baseline value, it calculates the aerodynamic response coefficient in reverse. After determining the current operating condition type, it automatically calls the decoupling logic matching that type for calculation, ultimately outputting a unique aerodynamic response coefficient as the result of this step. Regardless of how this aerodynamic response coefficient is obtained, it has a unified physical meaning: the current response amplitude caused by a unit change in theoretical load characterization value, representing the efficiency of the fan impeller in doing work on the airflow under the current flow field structure.

[0068] The technical solution provided by the above embodiments can bring at least the following beneficial effects: This embodiment constructs a data sequence consisting of theoretical load characterization values ​​and active current at the current time and multiple historical times, and identifies the current operating condition type of the autoclave based on the fluctuation degree of the theoretical load characterization values ​​in the sequence. Then, it selects a matching decoupling method to determine the aerodynamic response coefficient according to different operating condition types. It fully considers the different characteristics of the autoclave in the dynamic adjustment stage and steady-state pressure holding stage during actual operation, and ensures a reliable aerodynamic response coefficient under any operating condition by adaptively switching decoupling strategies. This avoids the problem of a single decoupling method failing under specific operating conditions, significantly improving the robustness and engineering practicality of the control method.

[0069] In one possible implementation, the process of determining the decoupling method that matches the operating condition type based on the above-mentioned operating condition type and determining the aerodynamic response coefficient can be specifically implemented through the following S401-S403, which will be explained in detail below.

[0070] S401. When the operating condition is dynamic, perform linear regression analysis on multiple data pairs in the data sequence and determine the slope of the linear regression line as the aerodynamic response coefficient.

[0071] Among them, dynamic operating conditions refer to operating conditions in which the fluctuation of the theoretical load characterization value in the data sequence meets the data conditions for regression analysis.

[0072] In one possible implementation, when it is determined that the current operating condition is dynamic, it indicates that the theoretical load characteristics in the data sequence have sufficient dispersion to meet the data conditions for regression analysis. In this case, the least squares method is used to perform univariate linear regression analysis on multiple data pairs in the data sequence to statistically separate the current component that changes linearly with the theoretical load characteristics.

[0073] For example, firstly, the variance of the theoretical load characterization value in the data sequence is calculated, then the covariance between the theoretical load characterization value and the active current is calculated, and finally, based on the least squares principle, the ratio of the covariance to the variance is determined as the slope of the linear regression line. This aerodynamic response coefficient characterizes the magnitude of the increase in active current when the theoretical load characterization value increases by one unit. Since the influence of constant terms such as mechanical friction is excluded, this coefficient directly reflects the efficiency of the fan impeller in doing work on the airflow. The larger the coefficient, the stronger the current response caused by the same theoretical load change, that is, the greater the reaction force of the airflow on the impeller and the more effective the flow field structure; the smaller the coefficient, the lower the efficiency of the airflow doing work, which may indicate poor flow or airflow short circuit.

[0074] In one possible implementation, when the current operating condition is determined to be dynamic, the intercept of the linear regression line is used as the mechanical loss baseline. This mechanical loss baseline characterizes the current that the motor still needs to consume to overcome mechanical friction when the theoretical load is zero, reflecting the energy loss caused by mechanical structures such as bearing friction and wind resistance. This mechanical loss baseline and its corresponding current gas temperature are stored as reference data for temperature compensation correction under subsequent steady-state operating conditions.

[0075] S402. When the operating condition is steady state, obtain the preset mechanical loss base value, perform temperature compensation correction on the mechanical loss base value based on the current gas temperature, and determine the corrected mechanical loss base value.

[0076] In one possible implementation, when the steady-state condition is determined based on the fluctuation of the theoretical load characterization values ​​in the data sequence, it indicates that the theoretical load characterization values ​​in the data sequence are too clustered, making it impossible to directly separate the aerodynamic response coefficient and the mechanical loss baseline value through linear regression analysis. In this case, a reverse calculation method based on temperature compensation correction is adopted. First, a preset mechanical loss baseline value is obtained, and then it is corrected according to the current gas temperature to eliminate mechanical friction drift caused by temperature changes.

[0077] For example, a preset mechanical loss baseline value is retrieved from the internal storage unit. This preset mechanical loss baseline value is determined through linear regression analysis under dynamic operating conditions during historical operation, representing the current component corresponding to mechanical friction loss at a certain historical moment, and is stored together with its corresponding temperature value. Because changes in ambient temperature during long-term operation of the autoclave cause changes in the viscosity of the motor bearing grease, leading to changes in mechanical friction resistance, the grease viscosity decreases as the temperature rises, reducing mechanical friction resistance and consequently decreasing the mechanical loss baseline value; conversely, the opposite occurs when the temperature decreases. Therefore, directly using the mechanical loss baseline value from a historical moment for reverse calculation at the current moment will produce errors. To solve this problem, the preset mechanical loss baseline value is corrected for temperature compensation based on the gas temperature at the current moment. The basic principle of the correction is to utilize the physical law of mechanical friction changing with temperature, and to adaptively adjust the baseline value according to the degree of deviation of the current temperature from the historical temperature corresponding to the mechanical loss baseline value. The specific implementation of temperature compensation correction can be a linear compensation model, which assumes that within a certain temperature range, the change in the mechanical loss baseline value is proportional to the temperature change, with the proportionality coefficient being a preset mechanical resistance temperature coefficient. This coefficient reflects the sensitivity of mechanical friction to temperature. Through this correction, a corrected mechanical loss baseline value that accurately reflects the true level of mechanical friction under the current temperature conditions can be obtained, serving as the input parameter for subsequent back-calculation of the aerodynamic response coefficient.

[0078] S403. Determine the aerodynamic response coefficient based on the current active current, theoretical load characterization value, and corrected mechanical loss base value.

[0079] In one possible implementation, after obtaining the corrected mechanical loss baseline value, the aerodynamic response coefficient under the current steady-state condition is determined by reverse calculation, combining the active current at the current moment with the theoretical load characterization value.

[0080] For example, aerodynamic response coefficients under dynamic operating conditions The following formula 2 is satisfied:

[0081] Formula 2

[0082] in, This represents the active current at the current moment; The theoretical load representation value at the current moment; The corrected mechanical loss baseline value is used; by subtracting the corrected mechanical loss baseline value (i.e., the mechanical friction component at the current temperature) from the current total active current, the current increment purely caused by the aerodynamic load is obtained. This increment is then divided by the current theoretical load characterization value to obtain the aerodynamic current increment corresponding to a unit theoretical load characterization value, which is the aerodynamic response coefficient. .

[0083] Understandably, before the actual calculation, it is first determined whether the theoretical load characterization value at the current moment is greater than the preset minimum effective load threshold (for example, the minimum effective load threshold is set to 0.1). If the theoretical load characterization value at the current moment is greater than the preset minimum effective load threshold, it indicates that the fan is in an effective operating state, and the aerodynamic response coefficient is calculated according to the formula; if the theoretical load characterization value at the current moment is not greater than the preset minimum effective load threshold, it indicates that the fan load is extremely low or has been shut down. In this case, the aerodynamic response coefficient is forcibly set to zero, and the subsequent flow field evaluation steps are skipped to avoid calculation anomalies.

[0084] The technical solution provided by the above embodiments can bring at least the following beneficial effects: This embodiment designs differentiated methods for determining aerodynamic response coefficients for dynamic and steady-state operating conditions: Under dynamic operating conditions, the slope of the regression line is directly determined as the aerodynamic response coefficient by performing linear regression analysis on the data sequence; under steady-state operating conditions, a preset mechanical loss base value is obtained and temperature compensation correction is performed by combining the current gas temperature, and then the aerodynamic response coefficient is calculated in reverse based on the corrected mechanical loss base value, active current, and theoretical load characterization value. Under dynamic operating conditions, the information redundancy caused by data fluctuations is fully utilized, and the aerodynamic response coefficient and mechanical loss base value are effectively separated through regression analysis; under steady-state operating conditions, the mechanical loss drift problem caused by the change in bearing grease viscosity with temperature is solved by the temperature compensation mechanism, ensuring that accurate aerodynamic response coefficients can still be obtained even when data fluctuations are insufficient. The two methods complement each other and jointly construct a complete decoupled system covering all operating conditions.

[0085] In one possible implementation, when the flow field is determined to be in a healthy state, the aerodynamic response coefficient corresponding to the gas temperature needs to be used as a reference response coefficient and stored in the health benchmark library. This process can be implemented through the following S501-S502, which will be explained in detail below.

[0086] S501. When the gas pressure is lower than the preset safe pressure threshold, determine that the flow field is in a healthy state.

[0087] In one possible implementation, the gas pressure is monitored in real time during the operation of the autoclave, and the current gas pressure is compared with a preset safe pressure threshold to determine whether the current flow field is in a healthy state that can be used to establish a health benchmark.

[0088] For example, the safe pressure threshold is a pre-calibrated pressure constant used to define the boundary between the low-pressure healthy stage and the high-pressure potential risk stage. Its determination is based on the following principles of fluid mechanics: Under low-pressure conditions, gas density is low, fluid inertia is small, and airflow can naturally form deep circulation following the structure of the air guide shroud, penetrating the mold area without short-circuiting. Through extensive experimental calibration, when the pressure inside the tank is below 0.2 MPa, regardless of the fan speed adjustment, the airflow can maintain a healthy flow state and will not experience airflow short-circuiting due to excessive inertia. Therefore, using 0.2 MPa as the safe pressure threshold ensures that the flow field data collected below this pressure corresponds to a healthy state. After acquiring the gas pressure at the current moment in each control cycle, it is compared with the safe pressure threshold. If the gas pressure is less than the safe pressure threshold, it indicates that the current pressure inside the tank is below the safe threshold, and the system is in a low-pressure operation stage. At this time, the gas density is low, the fluid inertia is small, and the airflow can usually form a healthy deep circulation; the flow field structure is considered healthy. Based on this physical law, the current flow field is determined to be in a healthy state, triggering the subsequent health baseline data acquisition and storage process. If the gas pressure is greater than or equal to the safe pressure threshold, it indicates that the system has entered a high-pressure condition, and the flow field is at risk of short circuit. At this time, health baseline data acquisition is no longer performed, and the system proceeds to the health baseline query and application stage.

[0089] S502. Using gas temperature as an index, store the aerodynamic response coefficient corresponding to the gas temperature as a reference response coefficient in the health benchmark library.

[0090] In one possible implementation, after determining that the current flow field is in a healthy state based on pressure comparison, the aerodynamic response coefficient at the current moment is associated with the gas temperature at the current moment and stored to construct a health benchmark database indexed by temperature, which is used to record the aerodynamic response characteristics of the flow field in a healthy state at different temperatures.

[0091] For example, the current gas temperature and aerodynamic response coefficient are first obtained. Since the pressure is below the safe pressure threshold, the flow field is considered healthy. Therefore, the aerodynamic response coefficient represents the aerodynamic response level that the flow field should have in a healthy state at the current temperature. Using the current gas temperature as the index key, the current aerodynamic response coefficient is stored as the reference response coefficient corresponding to that temperature in the healthy benchmark library. The healthy benchmark library is a data storage structure, which can be logically represented as a temperature-reference response coefficient mapping table. For each temperature value, the library stores a corresponding reference response coefficient value, characterizing the standard aerodynamic response characteristics of a healthy flow field under that temperature condition. In the actual storage process, it is first checked whether a record corresponding to the current temperature already exists in the healthy benchmark library. If it does not exist, the current aerodynamic response coefficient is directly stored as a new record in the library. If a record already exists, it indicates that a reference response coefficient has been stored at the same or similar temperature in previous operating cycles. To improve the robustness of the benchmark and avoid the impact of single measurement errors on the benchmark library, a weighted average method is used to update the original records. This update strategy allows newly collected health data to gradually correct the original baseline values ​​with a smaller weight, ensuring that the baseline library can adapt to equipment aging and environmental changes, while avoiding excessive impact on the baseline library from a single abnormal data point.

[0092] The technical solution provided by the above embodiments can bring at least the following beneficial effects: In this embodiment, during the low-pressure stage when the gas pressure is lower than a preset safe pressure threshold, the aerodynamic response coefficient at the corresponding moment is stored as a reference response coefficient in the health benchmark library using gas temperature as an index, thereby establishing benchmark information reflecting the characteristics of a healthy flow field. It cleverly utilizes the physical laws governing the formation of healthy circulation in the low-pressure stage, and constructs a benchmark library that matches the equipment's own characteristics and process conditions through self-learning, avoiding deviations caused by using fixed theoretical or empirical values. This provides an accurate and reliable comparison benchmark for subsequent flow field state assessment under high-pressure conditions, and also gives the method good equipment and process adaptability.

[0093] In one possible implementation, the process of determining the cyclic short-circuit ratio based on the aerodynamic response coefficient and preset benchmark information reflecting the characteristics of a healthy flow field can be specifically implemented through the following S601-S603, which will be described in detail below.

[0094] S601. Based on the current gas temperature, determine the corresponding reference response coefficient from the health benchmark library.

[0095] In one possible implementation, once the autoclave enters high-pressure operation, the health benchmark library is no longer updated. Instead, a reference response coefficient corresponding to the current temperature is obtained by querying or interpolating from the established health benchmark library based on the current gas temperature, which serves as a comparison benchmark for subsequent flow field health assessment.

[0096] For example, the real-time gas temperature is acquired during the current control cycle and used as a query index in the health benchmark database. When searching the health benchmark database based on the current temperature, the following three scenarios exist:

[0097] 1. Temperature matching: If a record with the exact same temperature as the current temperature already exists in the health benchmark library, the reference response coefficient corresponding to that record will be directly retrieved and used as the reference response coefficient at the current temperature.

[0098] 2. If the temperature lies between two known temperature points, and the current temperature falls between two adjacent temperature records in the database, then linear interpolation is used to calculate the reference response coefficient corresponding to the current temperature. Linear interpolation is based on the assumption that, within a small temperature range, the aerodynamic response coefficient of a healthy flow field changes approximately linearly with temperature. This assumption is reasonable in engineering because physical properties such as gas viscosity can change approximately linearly over a finite temperature range.

[0099] 3. Temperature exceeds the range recorded in the database. If the current temperature is lower than the minimum temperature recorded in the database or higher than the maximum temperature recorded in the database, a reference response coefficient cannot be obtained through interpolation. In this case, the following strategy is adopted: if the deviation is small, the recorded value of the nearest endpoint is used as the reference response coefficient; if the deviation is large, the reference response coefficient of the previous control cycle is maintained unchanged to ensure the continuity of control. At the same time, a prompt message can be issued, suggesting data collection during the low-pressure phase over a wider temperature range to improve the coverage of the health baseline database.

[0100] The reference response coefficient obtained in the above manner represents the theoretically required aerodynamic response capability for a healthy flow state under low pressure at the current temperature. This value will be used as input for subsequent steps, compared with the aerodynamic response coefficient at the current moment, and combined with the pressure correction factor to calculate the cycle short-circuit ratio.

[0101] S602. Based on the gas pressure at the current moment, determine the pressure correction factor used to compensate for the difference in fluid characteristics between the high-pressure condition and the low-pressure reference.

[0102] In one possible implementation, after obtaining the reference response coefficient, a pressure correction factor is further determined based on the gas pressure at the current moment to eliminate the comparison deviation between the high-pressure operating condition and the low-pressure reference operating condition caused by the difference in fluid characteristics.

[0103] For example, because increased gas pressure leads to a significant increase in gas density, which in turn affects fluid dynamics, the aerodynamic response coefficient under high-pressure conditions will inherently differ from the reference response coefficient under low-pressure conditions, even when the flow field structure is exactly the same. Therefore, the aerodynamic response coefficient under the current high-pressure condition cannot be directly compared numerically with the reference response coefficient established during the low-pressure phase. Based on the current gas pressure and combined with preset pressure compensation parameters, a correction factor corresponding to the current pressure is determined. This correction factor reflects the expected change in the aerodynamic response level of the healthy flow field from the low-pressure reference to the current pressure condition. Multiplying the reference response coefficient by this pressure correction factor yields the expected aerodynamic response value of the healthy flow field under the current pressure condition, laying the foundation for subsequent comparisons with the actual aerodynamic response coefficients.

[0104] S603. Based on the aerodynamic response coefficient, reference response coefficient, and pressure correction factor, determine the cyclic short-circuit ratio.

[0105] In one possible implementation, after obtaining the aerodynamic response coefficient at the current moment, the reference response coefficient obtained based on the current temperature, and the pressure correction factor determined based on the current pressure, the three are fused together to obtain the cyclic short-circuit ratio used to quantify the degree of failure of the current flow field.

[0106] For example, the reference response coefficient is first combined with a pressure correction factor to obtain the pressure-corrected health baseline expectation value. This expectation value represents the theoretically achievable aerodynamic response level for a healthy flow field under current temperature and pressure conditions. Then, the actual aerodynamic response coefficient at the current moment is compared with this health baseline expectation value, and the relative deviation between the two is calculated. When the actual aerodynamic response coefficient is close to the health baseline expectation value, it indicates that the flow field structure is effective, and the airflow can fully penetrate the mold area for circulating heat exchange; at this time, the circulation short-circuit ratio approaches its minimum. When the actual aerodynamic response coefficient is significantly less than the health baseline expectation value, it indicates that there is an airflow short-circuit phenomenon in the flow field; the gas does not effectively flow through the mold area and directly returns to the fan intake. At this time, the circulation short-circuit ratio increases, and the greater the deviation, the higher the ratio. Through this calculation process, multi-dimensional flow field state information is integrated into a dimensionless index between 0 and 1, which intuitively reflects the degree of failure of the current flow field relative to its healthy state.

[0107] The technical solution provided by the above embodiments can bring at least the following beneficial effects: When determining the cycle short-circuit ratio in this embodiment, the corresponding reference response coefficient is obtained from the health benchmark library based on the gas temperature at the current moment. At the same time, a pressure correction factor is determined based on the gas pressure at the current moment to compensate for the difference in fluid characteristics between the high-pressure condition and the low-pressure benchmark. Finally, the cycle short-circuit ratio is calculated by combining the aerodynamic response coefficient, the reference response coefficient, and the pressure correction factor. By introducing the pressure correction factor, the problem of fluid characteristic differences caused by gas density changes under high-pressure conditions is effectively solved. This allows the health benchmark established based on the low-pressure stage to be reasonably mapped to the high-pressure condition for comparison, ensuring the comparability and scientific validity of the cycle short-circuit ratio index under different pressure conditions, thereby truly and accurately reflecting the degree of failure of the flow field structure.

[0108] In one possible implementation, the process of determining the pressure correction factor based on the current gas pressure to compensate for the difference in fluid characteristics between the high-pressure condition and the low-pressure reference can be specifically implemented through the following S701-S702, which will be described in detail below.

[0109] S701, Obtain the preset pressure compensation coefficient.

[0110] In one possible implementation, before determining the pressure correction factor, a preset pressure compensation coefficient is first obtained from the internal storage unit. This coefficient is used to quantify the degree of influence of a unit pressure change on the aerodynamic response characteristics.

[0111] For example, the pressure compensation coefficient is 0.1 / MPa. This coefficient is an empirical constant obtained through experimental calibration, with dimensions being the reciprocal of the pressure unit. It reflects the relative rate of change of the aerodynamic response coefficient of the healthy flow field caused by a one-unit change in gas pressure under typical operating conditions of the autoclave. The specific value of the pressure compensation coefficient is related to various factors such as the structural dimensions of the autoclave, the geometry of the air hood, and the gas properties. It is typically determined during the equipment commissioning phase by comparing aerodynamic response data under different pressures and stored as a fixed parameter in non-volatile memory. Each time the pressure correction factor is calculated, this preset value is directly read as the input parameter for subsequent calculations.

[0112] S702. Based on the pressure difference between the current gas pressure and the preset safe pressure threshold, and the pressure compensation coefficient, determine the pressure correction factor.

[0113] In one possible implementation, after obtaining the preset pressure compensation coefficient, a pressure correction factor is calculated to compensate for the difference in fluid characteristics between the high-pressure condition and the low-pressure reference, taking into account the difference between the current gas pressure and the safe pressure threshold.

[0114] For example, pressure correction factor The following formula 3 is satisfied:

[0115] Formula 3

[0116] in, The preset pressure compensation coefficient characterizes the relative rate of change of aerodynamic response for every 1 Pa change in pressure; The current gas pressure; This is the preset safety pressure threshold.

[0117] Formula 3 uses a linear compensation model to calculate the pressure correction factor. First, it calculates the pressure difference between the current pressure and the safety threshold, multiplies it by the pressure compensation coefficient to obtain the relative change caused by the pressure, and adds a baseline value of 1 to obtain the correction factor. When the current pressure is higher than the safety threshold, the pressure difference is positive, and the correction factor is greater than 1; when the current pressure is lower than the safety threshold, the pressure difference is negative, the correction factor is less than 1, and the correction factor is forcibly set to 1 (but no pressure correction is performed during low-pressure phases). Pressure Correction Factor It is a bridge that maps the health benchmark established in the low-pressure stage to the high-pressure operating condition. Its physical meaning is the factor by which the healthy reference response coefficient should be magnified relative to the low-pressure benchmark under the current pressure.

[0118] The technical solution provided by the above embodiments can bring at least the following beneficial effects: In determining the pressure correction factor, this embodiment obtains a preset pressure compensation coefficient and calculates the pressure correction factor based on the pressure difference between the current gas pressure and the preset safe pressure threshold, as well as the compensation coefficient. It provides a simple and effective method for determining the pressure correction factor, achieving a smooth transition between high-pressure conditions and low-pressure references through a linear compensation model. This ensures both the simplicity of calculation and a good reflection of the influence of pressure changes on fluid characteristics, providing a reliable prerequisite for the accurate calculation of the circulation short-circuit ratio.

[0119] In one possible implementation, the process of determining the cyclic short-circuit ratio based on the aerodynamic response coefficient, the reference response coefficient, and the pressure correction factor can be specifically implemented through the following S801-S802, which will be described in detail below.

[0120] S801. Based on the reference response coefficient and the pressure correction factor, determine the pressure-corrected reference response coefficient.

[0121] In one possible implementation, after obtaining the reference response coefficient and the pressure correction factor, the two are fused to obtain a healthy baseline expectation value applicable to the current pressure conditions, which serves as a benchmark for subsequent comparison with the actual aerodynamic response coefficient.

[0122] For example, the reference response coefficient represents the aerodynamic response level at a given temperature under low-pressure healthy operating conditions; the pressure correction factor characterizes the expected amplification factor from the low-pressure reference to the aerodynamic response level of the healthy flow field under the current pressure conditions; multiplying the reference response coefficient by the pressure correction factor yields the pressure-corrected reference response coefficient. This product represents the theoretically expected aerodynamic response value that should be achieved under the current temperature and pressure conditions, assuming the flow field remains healthy. For instance, if the reference response coefficient is 0.8 and the pressure correction factor is 1.2, the pressure-corrected reference response coefficient is 0.96, meaning that the aerodynamic response level of the healthy flow field should reach 0.96 under the current high-pressure conditions. This expected value comprehensively considers the influence of temperature on aerodynamic characteristics (reflected by the reference response coefficient) and the influence of pressure on aerodynamic characteristics (reflected by the pressure correction factor), providing an accurate benchmark for subsequent comparisons with actual aerodynamic response coefficients.

[0123] S802. Determine the cyclic short-circuit ratio based on the aerodynamic response coefficient and the corrected reference response coefficient.

[0124] In one possible implementation, after obtaining the current aerodynamic response coefficient and the pressure-corrected reference response coefficient, the two are compared and calculated to obtain the cyclic short-circuit ratio used to quantify the degree of failure of the current flow field.

[0125] For example, the circulation short-circuit ratio is a dimensionless index between 0 and 1, whose value directly reflects the degree of deviation of the current flow field from a healthy state. The calculation is based on the following logic: First, the aerodynamic response coefficient at the current moment is compared with the pressure-corrected reference response coefficient to obtain the relative level of the actual aerodynamic response to the expected value of the healthy baseline; then, 1 is subtracted from this ratio to obtain the negative deviation of the actual aerodynamic response from the healthy baseline; finally, the calculation result is compared with 0, and the maximum value of the two is taken as the final circulation short-circuit ratio. This calculation logic ensures that the circulation short-circuit ratio is always non-negative, and its value range is limited to between 0 and 1. When the actual aerodynamic response coefficient is close to the pressure-corrected reference response coefficient, the ratio of the two is close to 1; 1 minus this ratio is close to 0. At this point, the circulation short-circuit ratio approaches 0, indicating that the current flow field structure is effective, the airflow can fully penetrate the mold area for circulating heat exchange, and the flow field is in a healthy state. When the actual aerodynamic response coefficient is significantly smaller than the pressure-corrected reference response coefficient, the ratio between the two is much less than 1. Subtracting this ratio from 1 results in a value close to 1. At this point, the circulation short-circuit ratio approaches 1, indicating a severe airflow short-circuit phenomenon in the current flow field. The gas does not effectively flow through the mold area and returns directly to the fan intake, indicating a severe flow field failure. When the actual aerodynamic response coefficient is slightly larger than the pressure-corrected reference response coefficient due to calculation errors or abnormal data, the ratio between the two is greater than 1. Subtracting this ratio from 1 results in a negative value. In this case, 0 is taken as the circulation short-circuit ratio to avoid the occurrence of negative values.

[0126] The technical solution provided by the above embodiments can bring at least the following beneficial effects: In determining the circulation short-circuit ratio, this embodiment first determines the pressure-corrected reference response coefficient based on the reference response coefficient and the pressure correction factor, and then calculates the circulation short-circuit ratio based on the aerodynamic response coefficient and the corrected reference response coefficient. By first correcting the reference value and then comparing it, the influence of pressure on fluid characteristics is fully reflected in the reference value adjustment stage, so that the final circulation short-circuit ratio can intuitively reflect the degree of deviation of the current flow field state from the theoretical healthy state. The larger the value of this index, the more serious the airflow short-circuit, thus providing a clear and definite target guidance for subsequent speed control.

[0127] In one possible implementation, the process of obtaining a preset mechanical loss base value when the operating condition is a steady-state condition, performing temperature compensation correction on the mechanical loss base value based on the current gas temperature, and determining the corrected mechanical loss base value can be specifically implemented through the following S901-S902, which will be explained in detail below.

[0128] S901, Obtain the preset temperature coefficient of mechanical resistance.

[0129] In one possible implementation, before performing temperature compensation correction, a preset mechanical resistance temperature coefficient is first obtained from the internal storage unit. This coefficient is used to quantify the degree of influence of temperature changes on mechanical friction loss.

[0130] For example, the temperature coefficient of mechanical resistance is an empirical constant obtained through experimental calibration, and its dimension is the reciprocal of the temperature unit, such as K. -1 This coefficient reflects the characteristic of the viscosity of motor bearing grease changing with temperature. As temperature increases, the grease viscosity decreases, reducing mechanical friction resistance and leading to a decrease in the base value of mechanical losses; conversely, the opposite occurs when temperature decreases. For example, the temperature coefficient of mechanical resistance is -5 × 10⁻⁶. -4 / K. The physical meaning of this value is: for every 1 Kelvin increase in temperature, the base value of mechanical loss decreases by 0.05%. This coefficient was determined during the equipment commissioning phase by measuring the change in no-load current at different temperatures and is stored as a fixed parameter in non-volatile memory. Each time temperature compensation correction is performed under steady-state conditions, this preset value is directly read as the input parameter for subsequent calculations.

[0131] S902. Based on the temperature difference between the current gas temperature and the reference temperature corresponding to the mechanical loss base value, as well as the mechanical resistance temperature coefficient, the mechanical loss base value is compensated to determine the corrected mechanical loss base value.

[0132] In one possible implementation, after obtaining the preset mechanical resistance temperature coefficient, the historically latched mechanical loss base value is quantitatively compensated by combining the difference between the current gas temperature and the reference temperature corresponding to the mechanical loss base value, so as to obtain the corrected mechanical loss base value that can accurately reflect the true level of mechanical friction under the current temperature conditions.

[0133] For example, the corrected mechanical loss baseline value The following formula 4 is satisfied:

[0134] Formula 4

[0135] in, This is the base value for mechanical loss; Temperature coefficient of mechanical resistance; The current gas temperature; The temperature at the historical moment corresponding to the baseline value of mechanical loss; A preset lower limit clamping coefficient (exemplarily set to 0.1) is used to prevent the corrected mechanical loss base value from being too small or negative. A preset upper limit clamping coefficient (exemplarily set to 2.0) is used to prevent overcompensation due to sensor malfunctions; under normal operating conditions, Within the specified range, the clamping logic is inactive; protection is only triggered in extreme situations such as sensor malfunctions to ensure the stability of the control system.

[0136] Formula 4 employs a linear compensation model to correct the mechanical loss baseline value for temperature. First, the temperature difference between the current temperature and the historical temperature corresponding to the mechanical loss baseline value is calculated. This difference is multiplied by a temperature coefficient to obtain the relative rate of change caused by temperature. Adding 1 yields the temperature compensation coefficient, which is then multiplied by the mechanical loss baseline value to obtain the corrected baseline value. When the current temperature is higher than the historical temperature corresponding to the mechanical loss baseline value, the temperature difference is positive. If the temperature coefficient is negative (indicating that the grease viscosity decreases and mechanical resistance decreases with increasing temperature), the compensation coefficient is less than 1, and the corrected baseline value decreases; conversely, the same applies. This model assumes that mechanical loss changes linearly with temperature, conforming to the physical law of bearing grease viscosity changing with temperature.

[0137] The technical solution provided by the above embodiments can bring at least the following beneficial effects: When performing temperature compensation correction on the mechanical loss base value under steady-state operating conditions, this embodiment obtains a preset mechanical resistance temperature coefficient and performs compensation based on the temperature difference between the current gas temperature and the reference temperature corresponding to the mechanical loss base value, as well as this temperature coefficient. It fully considers the influence of temperature changes on mechanical friction resistance during long-term operation of the autoclave, and effectively eliminates the mechanical loss drift error caused by changes in bearing grease viscosity by introducing a temperature compensation mechanism. This ensures that the aerodynamic response coefficient obtained by reverse calculation under steady-state operating conditions still maintains high accuracy, further improving the adaptability of the entire control method in variable temperature environments.

[0138] Please see Figure 2This diagram illustrates a system architecture of a top air circulation control system 200 for an autoclave according to an embodiment of the present invention. This system implements the aforementioned top air circulation control method for an autoclave. The system includes: a data acquisition module 201 for acquiring the operating status parameters of the autoclave; the operating status parameters include at least: gas pressure, gas temperature, fan speed, and motor active current; a theoretical load determination module 202 for determining a theoretical load characterization value based on gas pressure, gas temperature, and fan speed; the theoretical load characterization value characterizes the theoretical driving intensity applied by the fan to the gas; and a parameter decoupling module 203 for determining the theoretical load based on the theoretical load table. The system uses eigenvalues ​​and active current to dynamically decouple the mechanical loss component used to overcome mechanical friction from the aerodynamic load component used to drive gas flow, thus determining the aerodynamic response coefficient. The aerodynamic response coefficient characterizes the effectiveness of the flow field structure. The state quantification module 204 determines the cyclic short-circuit ratio based on the aerodynamic response coefficient and preset benchmark information reflecting the characteristics of a healthy flow field. The cyclic short-circuit ratio quantifies the current degree of flow field failure. The control adjustment module 205 adjusts the fan speed to a target speed based on the cyclic short-circuit ratio using an extreme value search strategy. The target speed is the speed corresponding to when the cyclic short-circuit ratio approaches its minimum value.

[0139] The technical solution provided in the above embodiments can bring at least the following beneficial effects: This embodiment, by constructing a top air circulation control system for an autoclave that includes a data acquisition module, a theoretical load determination module, a parameter decoupling module, a state quantification module, and a control adjustment module, achieves fully automated control from acquiring operating state parameters, calculating theoretical load characterization values, dynamically decoupling current signals, quantifying flow field failure levels, to adaptively adjusting fan speed. Through the collaborative work of each module, this system transforms the complex problem of flow field state identification and optimal speed search into a modular solution that can be engineered. It not only effectively suppresses airflow short-circuiting under high-pressure conditions and improves the uniformity of the temperature field inside the autoclave, but also possesses good scalability and maintainability, providing complete technical support for the intelligent upgrading of autoclave equipment.

[0140] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0141] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for controlling the top air circulation of an autoclave, characterized by, The method comprises: acquiring an operating state parameter of the autoclave; the operating state parameter at least comprises: gas pressure, gas temperature, fan rotating speed and active current of the motor; determining a theoretical load characteristic value based on the gas pressure, the gas temperature and the fan rotating speed; the theoretical load characteristic value is used to represent a theoretical driving strength of the fan to the gas; based on the theoretical load characteristic value and the active current, dynamically decoupling a mechanical loss component in the active current for overcoming mechanical friction from a pneumatic load component for driving the gas flow, and determining a pneumatic response coefficient, comprising: constructing a data sequence based on a current time data pair and a plurality of historical time data pairs; the data pair is composed of the theoretical load characteristic value and the active current; determining an operating condition type of the autoclave at the current time based on a fluctuation degree of the theoretical load characteristic value in the data sequence; determining a decoupling mode matched with the operating condition type based on the operating condition type to decouple and determine the pneumatic response coefficient; when the operating condition type is a dynamic condition, performing linear regression analysis on a plurality of the data pairs in the data sequence, and determining a slope of a linear regression straight line as the pneumatic response coefficient; the dynamic condition is a condition in which the fluctuation degree of the theoretical load characteristic value in the data sequence meets a data condition for regression analysis; when the operating condition type is a steady state condition, acquiring a preset mechanical loss base value, performing temperature compensation correction on the mechanical loss base value based on the gas temperature at the current time, and determining a corrected mechanical loss base value; the steady state condition is a condition in which the fluctuation degree of the theoretical load characteristic value in the data sequence is insufficient to support effective regression analysis; determining the pneumatic response coefficient based on the active current at the current time, the theoretical load characteristic value and the corrected mechanical loss base value; the pneumatic response coefficient is used to represent effectiveness of the flow field structure; when the gas pressure is lower than a preset safety pressure threshold, determining that the flow field is in a healthy state; based on the pneumatic response coefficient and preset reference information reflecting the characteristics of the healthy flow field, determining a cycle short circuit ratio; the cycle short circuit ratio is used to quantify the failure degree of the current flow field; the cycle short circuit ratio is determined based on the following logic: first, performing ratio operation on the pneumatic response coefficient at the current time and the reference response coefficient after pressure correction, then subtracting the ratio from 1 to obtain the negative deviation degree of the actual pneumatic response from the healthy reference; finally, comparing the calculation result with 0, and taking the maximum value of the two as the cycle short circuit ratio; based on the cycle short circuit ratio, adjusting the rotating speed of the fan to a target rotating speed by using an extreme value search strategy; the target rotating speed is the rotating speed corresponding to the minimum value of the cycle short circuit ratio.

2. The method of claim 1, wherein the method further comprises: The determination of the theoretical load characteristic value based on the gas pressure, the gas temperature and the fan rotating speed comprises: determining a theoretical gas load factor based on the gas pressure, the gas temperature and the fan rotating speed; the theoretical gas load factor is used to comprehensively reflect the coupling influence degree of the current gas density and the rotating speed on the driving strength of the fan; The theoretical gas load factor is determined as the theoretical load characterization value.

3. The method of claim 1, wherein the method further comprises: The method further comprises: The aerodynamic response coefficient corresponding to the gas temperature is stored in the health benchmark library as a reference response coefficient indexed by the gas temperature.

4. The method of claim 3, wherein the top air circulation is controlled by a temperature sensor and a pressure sensor. The method further comprises: The circulating short-circuit ratio is determined based on the aerodynamic response coefficient, the reference response coefficient, and a pressure correction factor. The reference response coefficient corresponding to the gas temperature is determined from the health benchmark library; The pressure correction factor is determined based on the gas pressure at the current time and a preset safety pressure threshold.

5. The method of claim 4, wherein the top air circulation is controlled by a temperature sensor and a pressure sensor. The circulating short-circuit ratio is determined based on the aerodynamic response coefficient and the corrected reference response coefficient. The pressure correction factor is determined based on the pressure difference between the gas pressure at the current time and the preset safety pressure threshold and the pressure compensation coefficient. The circulating short-circuit ratio is determined based on the aerodynamic response coefficient and the corrected reference response coefficient.

6. The method of claim 4, wherein the top air circulation is controlled by a temperature sensor and a pressure sensor. The method further comprises: The mechanical loss base value is temperature-compensated based on the gas temperature at the current time to determine a corrected mechanical loss base value. The mechanical loss base value is compensated based on the temperature difference between the gas temperature at the current time and a reference temperature corresponding to the mechanical loss base value and the mechanical resistance temperature coefficient to determine the corrected mechanical loss base value.

7. The method of claim 1, wherein the method further comprises: The system is configured to implement the method for controlling the top air circulation of a thermal compression tank according to any one of claims 1-7. The system comprises: A data acquisition module configured to acquire operating state parameters of the thermal compression tank, wherein the operating state parameters at least include gas pressure, gas temperature, fan speed, and active current of the motor.

8. A hot press top air circulation control system characterized by, A theoretical load determination module configured to determine a theoretical load characterization value based on the gas pressure, the gas temperature, and the fan speed, wherein the theoretical load characterization value is used to represent a theoretical driving strength of the fan on the gas. A parameter decoupling module configured to dynamically decouple a mechanical loss component used to overcome mechanical friction from an aerodynamic load component used to drive the gas flow in the active current based on the theoretical load characterization value and the active current, and determine an aerodynamic response coefficient, wherein the aerodynamic response coefficient is used to represent effectiveness of the flow field structure. A state quantification module configured to determine a circulating short-circuit ratio based on the aerodynamic response coefficient and preset benchmark information reflecting health of the flow field, wherein the circulating short-circuit ratio is used to quantify a failure degree of the current flow field. ​ ​ The control adjustment module is used to adjust the speed of the fan to a target speed based on the cyclic short-circuit ratio using an extreme value search strategy; the target speed is the speed corresponding to when the cyclic short-circuit ratio tends to the minimum value.

Images