Combined cooling control method for cooling metal casting

Abstract

The invention discloses a combined cooling control method for cooling a metal casting, which relates to the technical field of metal casting, and comprises the following steps: carrying out casting partition on the metal casting to establish a first casting area, a second casting area and a third casting area; executing temperature monitoring and establishing a verification data set; material information of the metal casting is obtained, cooling prediction fitting of the first casting area and the second casting area is carried out, verification updating is carried out, and an updated cooling prediction fitting result is generated; performing heat conduction analysis on the third casting area, and establishing a heat conduction influence fitting result; and configuring a cooling strategy of the balance critical area, establishing a flow parameter and a temperature parameter of a cooling medium, and executing cooling control of the third casting area. The technical problems that when a casting is cooled in the prior art, stress of critical areas of a rapid cooling area and a slow cooling area is concentrated, and the reliability and durability of the casting are low are solved, and the technical effect of improving the reliability and durability of the casting is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of metal casting, and particularly relates to a combined cooling control method for cooling metal castings. Background Art

[0002] With the continuous progress of industrial production and manufacturing technology, metal castings have been widely used in fields such as aerospace, automobile manufacturing, and machining. However, with the expansion of production scale and the complexity of the process flow, the cooling control process of metal castings is also facing increasing challenges. During the cooling process of metal castings, the rapid cooling area and the slow cooling area need to be cooled simultaneously. At this time, it becomes particularly crucial to handle the critical position between these two areas. The cooling process in the critical area will be affected by different cooling rates on both sides, which may lead to non-uniform microstructure and stress concentration, thereby affecting the overall quality and performance of the casting. Summary of the Invention

[0003] The present application provides a combined cooling control method for cooling metal castings, which is used to solve the technical problems that when cooling castings in the prior art, stress concentration occurs in the critical area between the rapid cooling area and the slow cooling area, resulting in low reliability and durability of the castings.

[0004] In view of the above problems, the present application provides a combined cooling control method for cooling metal castings.

[0005] In the first aspect of the present application, a combined cooling control method for cooling metal castings is provided. The method includes: Partition the metal casting to establish a first casting area, a second casting area, and a third casting area. Among them, the first casting area is the rapid cooling area, the second casting area is the slow cooling area, and the third casting area is the critical area between the first casting area and the second casting area; configure temperature monitoring sensors to perform temperature monitoring of the first casting area and the second casting area, and establish a verification data set; obtain the material information of the metal casting, perform cooling prediction fitting on the first casting area and the second casting area according to the material information and cooling medium information, and verify and update the cooling prediction fitting result through the verification data set to generate an updated cooling prediction fitting result; perform heat conduction analysis on the third casting area according to the updated cooling prediction fitting result to establish a heat conduction influence fitting result of the third casting area; configure a cooling strategy for balancing the critical area through the heat conduction influence fitting result to establish the flow rate parameter and temperature parameter of the cooling medium; perform cooling control on the third casting area according to the flow rate parameter and temperature parameter.

[0006] One or more technical solutions provided in the present application have at least the following technical effects or advantages: This application partitions the metal casting, establishing a first casting area, a second casting area, and a third casting area. Among them, the first casting area is a rapid cooling area, the second casting area is a slow cooling area, and the third casting area is the critical area between the first casting area and the second casting area; configure temperature monitoring sensors to monitor the temperatures of the first casting area and the second casting area, and establish a verification data set; obtain the material information of the metal casting, perform cooling prediction fitting for the first casting area and the second casting area based on the material information and the cooling medium information, and verify and update the cooling prediction fitting results through the verification data set to generate updated cooling prediction fitting results; perform heat conduction analysis on the third casting area according to the updated cooling prediction fitting results to establish the heat conduction influence fitting results of the third casting area; configure the cooling strategy for the balanced critical area through the heat conduction influence fitting results to establish the flow rate parameters and temperature parameters of the cooling medium; perform cooling control on the third casting area according to the flow rate parameters and temperature parameters. The present invention solves the technical problem that when the prior art cools the casting, stress concentration occurs in the critical area between the rapid cooling area and the slow cooling area, resulting in low reliability and durability of the casting. By performing heat conduction analysis, configuring a balanced cooling strategy, and performing cooling control, the technical effect of improving the reliability and durability of the casting is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0008] Figure 1 It is a schematic flow chart of the combined cooling control method for metal casting cooling provided by the embodiment of the present application; Figure 2 It is a schematic flow chart of abnormal management according to the cooling control abnormality in the combined cooling control method for metal casting cooling provided by the embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0009] The present application provides a combined cooling control method for metal casting cooling, which is used to solve the technical problem that when the prior art cools the casting, stress concentration occurs in the critical area between the rapid cooling area and the slow cooling area, resulting in low reliability and durability of the casting. By performing heat conduction analysis, configuring a balanced cooling strategy, and performing cooling control, the technical effect of improving the reliability and durability of the casting is achieved.

[0010] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0011] It should be noted that any variations of the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or server that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products, or devices.

[0012] Embodiment 1 As Figure 1 shown, the present application provides a combined cooling control method for cooling metal castings, and the method includes: Step S100: Divide the metal casting into casting zones to establish a first casting zone, a second casting zone, and a third casting zone. Among them, the first casting zone is a rapid cooling zone, the second casting zone is a slow cooling zone, and the third casting zone is the critical zone between the first casting zone and the second casting zone.

[0013] In the embodiments of the present application, to achieve precise and effective cooling control, the metal casting is divided into three different cooling zones: the first casting zone, the second casting zone, and the third casting zone. The first casting zone is a rapid cooling zone, and in this zone, high-efficiency cooling technologies such as forced air cooling or a water cooling system are used to rapidly reduce the temperature of the metal casting. The second casting zone is a slow cooling zone, and in this zone, relatively mild cooling methods such as natural air cooling or reducing the water flow rate are used to control the cooling rate. The third casting zone is the critical zone, located between the first casting zone and the second casting zone. Affected by the different cooling rates on both sides, it is a key part of the cooling process. Since the critical zone is affected by the different cooling rates on both sides, it is prone to temperature gradients and stress concentrations, resulting in non-uniform microstructures. It is necessary to ensure uniform cooling in the critical zone by real-time monitoring and adjusting the flow rate and temperature of the cooling medium to avoid stress concentration and non-uniform structures.

[0014] Step S200: Configure temperature monitoring sensors to perform temperature monitoring of the first casting zone and the second casting zone, and establish a verification data set.

[0015] In the embodiment of the present application, temperature sensors such as thermocouples, infrared temperature sensors or thermal resistors are respectively installed in the first casting area and the second casting area. The temperature of the first and second casting areas is monitored and recorded in real time by the temperature sensors. According to the dynamic characteristics of the cooling process, an appropriate sampling frequency is set. For example, the first casting area requires a higher sampling frequency to capture rapidly changing temperature data, which is set to once per second. The second casting area is set to once every 5 seconds.

[0016] Step S300: Obtain the material information of the metal casting, perform cooling prediction fitting for the first casting area and the second casting area according to the material information and the cooling medium information, and verify and update the cooling prediction fitting result through the verification data set to generate an updated cooling prediction fitting result.

[0017] In the embodiment of the present application, first, the material information of the metal material used for the casting, such as thermal conductivity, coefficient of thermal expansion, specific heat capacity, etc., is obtained by querying the material database. At the same time, the cooling medium information, including thermal conductivity, density, specific heat capacity, etc., is obtained by querying the material database. According to the material information of the metal casting and the cooling medium information, a fitting formula for the cooling process is constructed. Using the material and cooling medium information, cooling prediction fitting is performed for the first casting area and the second casting area. The cooling prediction fitting result is compared with the verification data set obtained by the temperature monitoring sensor. The error between the cooling prediction fitting result and the verification data set is calculated, such as mean square error, mean absolute error, etc. According to the comparison result, the thermal diffusivity, heat transfer coefficient, etc. are adjusted to reduce the error. For example, when the predicted temperature is generally too high, the initial temperature setting is increased or decreased. When the change rate of the predicted temperature is too fast, the thermal diffusivity or heat transfer coefficient is adjusted. The numerical simulation of the cooling process is re-performed using the corrected parameters to obtain an updated cooling prediction fitting result, and an updated cooling prediction fitting result is generated.

[0018] Step S400: Perform heat conduction analysis on the third casting area according to the updated cooling prediction fitting result, and establish a fitting result of the heat conduction influence of the third casting area.

[0019] In the embodiment of the present application, when performing the heat conduction analysis of the third casting region, the position heat conduction formula is used to describe the change of the temperature at a position in the third casting region over time. Using the updated cooling prediction results of the first and second casting regions, the boundary temperature conditions of the third casting region are set. These conditions are set through numerical simulation tools such as ANSYS and COMSOL. Numerical simulation is performed using finite element analysis software such as ANSYS and COMSOL. The position heat conduction formula, boundary conditions, and initial conditions are input into the simulation software for numerical calculation of the temperature field. The temperature distribution data of the third casting region is extracted from the numerical simulation results. Data processing software is used for data sorting and analysis. According to the numerical simulation results, a non-linear optimization algorithm such as the least squares method is used for parameter fitting to establish the fitting result of the heat conduction influence in the third casting region.

[0020] Step S500: Configure the cooling strategy for the balanced critical region through the fitting result of the heat conduction influence, and establish the flow rate parameter and temperature parameter of the cooling medium.

[0021] In the embodiment of the present application, the fitting result of the heat conduction influence in the third casting region is obtained from the previous heat conduction analysis. These results include the temperature changes at different positions and time points and their influence weight coefficients. At the same time, a cooling strategy is developed for the balanced critical region, and an appropriate cooling medium and cooling method are selected, such as forced convection cooling, natural convection cooling, or radiation cooling.

[0022] According to the fitting result of the heat conduction influence, the flow rate requirements of the cooling medium at different positions are preliminarily determined. The flow rate distribution of the cooling medium is calculated using the heat transfer formula. According to the temperature requirements of different regions, the preliminary temperature parameters of the cooling medium are set. Next, the flow rate parameter adjustment formula and temperature parameter adjustment formula of the cooling medium are configured, and the flow rate parameter and temperature parameter of the cooling medium are obtained through formula calculation.

[0023] Step S600: Perform the cooling control of the third casting region according to the flow rate parameter and temperature parameter.

[0024] In the embodiment of the present application, when performing the cooling control of the third casting region, by controlling the pump or valve of the cooling medium, ensure that the flow rate of the cooling medium reaches the set parameter value, and use a PID controller or other control algorithms to achieve precise flow rate control. Monitor the temperature of the cooling medium, and maintain the set temperature parameter by adjusting the supply temperature, flow rate of the coolant, or other parameters of the cooling system. Similarly, use a PID controller or other control algorithms to achieve stable temperature control. The cooling control of the third casting region is completed through this process.

[0025] Furthermore, step S300 in the method provided by the embodiment of the application further includes: Establish a fitting formula as follows: ; wherein, represents the fitting result of the cooling prediction varying with time, is the initial temperature of the casting, is time, which is the independent variable in the formula and is used to track the change of temperature with time, is the thermal diffusivity, is the Laplacian operator of temperature, is the heat transfer coefficient, is the specific heat capacity, is the flow rate of the cooling medium, is the temperature of the cooling medium, is the environmental impact function, which is used to describe the impact of environmental temperature on the system temperature; the cooling prediction fitting of the first casting area and the second casting area is carried out according to the fitting formula.

[0026] In the embodiment of the present application, the thermal diffusivity is calculated based on the thermal conductivity, density and specific heat capacity of the material, and is obtained by dividing the thermal conductivity by the product of density and specific heat capacity. The heat transfer coefficient is determined by searching electronic literature, which represents the heat transfer efficiency between the casting and the surrounding environment or the cooling medium. The specific heat capacity is obtained from the material database. According to the initial temperature of the casting, the initial temperature field is set. According to the flow rate and temperature of the cooling medium, and the environmental impact function, the boundary conditions are set. Using numerical simulation software, such as ANSYS, COMSOL, the fitting formula is input into the simulation environment to carry out the cooling prediction simulation of the first casting area and the second casting area.

[0027] Further, in the method provided by the embodiment of the application, for the heat conduction analysis of the third casting area according to the updated cooling prediction fitting result to establish the fitting result of the heat conduction influence of the third casting area, it further includes: Establish the position heat conduction formula as follows: ; wherein, represents the rate of change of the temperature with time at position in the third casting area, is the thermal diffusivity at position , is the second-order spatial derivative of the temperature at position , is the heat transfer coefficient at position , and are the influence weight coefficients of the first casting area and the second casting area on the position in the third interval area respectively, is the updated cooling prediction fitting result of the first casting area, is the updated cooling prediction fitting result for the second casting area, is the position of the third casting area at time the temperature; a heat conduction influence fitting result is established according to the position heat conduction formula.

[0028] In the embodiment of the present application, the thermal diffusivity and the heat transfer coefficient are obtained through the same process as described above. The influence weight coefficient is preset by technical experts based on requirements. Subsequently, numerical simulation software such as ANSYS and COMSOL is used to perform heat conduction analysis on the third casting area. During this process, according to the updated cooling prediction fitting result, the boundary conditions and initial conditions of the third casting area are set. After the numerical simulation is completed, the temperature distribution data of the third casting area is extracted from the results, and data processing software is used for data sorting and analysis. According to the numerical simulation results, a fitting tool such as the Curve Fitting Toolbox of MATLAB is used for data fitting to determine the specific values of the parameters in the position heat conduction formula. Through these steps, heat conduction analysis is performed on the third casting area using numerical simulation technology, data processing, and analysis tools to establish a heat conduction influence fitting result.

[0029] Further, in the method provided by the application embodiment, the cooling strategy of the balance critical area is configured through the heat conduction influence fitting result, and the flow rate parameter and temperature parameter of the cooling medium are established, further including: Configuring a flow rate parameter adjustment formula and a temperature parameter adjustment formula for the cooling medium, as follows: ; ; wherein, is the position of the third interval area at time the flow rate of the cooling medium, is the baseline flow rate at position ; is the flow rate adjustment coefficient at position ; is the temperature of the cooling medium at position at time ; is the baseline temperature at position ; is the temperature adjustment coefficient at position ; A flow rate parameter and a temperature parameter of the cooling medium are established according to the flow rate parameter adjustment formula and the temperature parameter adjustment formula.

[0030] In the embodiments of the present application, the heat conduction effect is used to affect the fitting result, and the baseline flow rate and the flow rate adjustment coefficient at each position are calculated. At the same time, the baseline temperature and the temperature adjustment coefficient at each position are calculated. When calculating, the baseline flow rate at position x is obtained by successively dividing the heat load at position x by the density of the cooling medium, the specific heat capacity of the cooling medium, and the temperature difference between the inlet and outlet of the cooling medium. The flow rate adjustment coefficient is obtained by dividing the difference between the maximum and minimum flow rates at position x by the maximum and minimum temperature change rates at position x. When calculating the baseline temperature, it is obtained by adding the inlet temperature of the cooling medium and successively dividing the heat load at position x by the density of the cooling medium, the specific heat capacity of the cooling medium, and the baseline flow rate at position x. When calculating the temperature adjustment coefficient, it is obtained by dividing the difference between the maximum and minimum temperatures at position x by the difference between the maximum and minimum temperature change rates at position x.

[0031] Through the flow rate parameter adjustment formula and the temperature parameter adjustment formula, according to the heat conduction effect fitting result and the real-time temperature data, the flow rate and temperature of the cooling medium are dynamically adjusted, and the flow rate parameters and temperature parameters of the cooling medium are established.

[0032] Furthermore, the method provided by the application embodiments further includes: Controlling and monitoring the cooling control, and establishing a monitoring data set; making a trigger determination based on the monitoring data set, where the trigger determination includes a temperature drop rate determination and a flow rate variation determination; if the temperature drop determination and / or the flow rate variation determination is activated, an abnormal cooling control is reported, and abnormal management is performed according to the abnormal cooling control.

[0033] In the embodiments of the present application, the cooling control is controlled and monitored through installed temperature sensors and flow rate sensors, and a monitoring data set is established. The monitoring data set includes information such as time stamps, positions, temperatures, and flow rates. Next, a trigger determination is made based on the monitoring data set to determine whether the temperature drop rate and the flow rate variation exceed the thresholds. When making the temperature drop rate determination, the temperature change rate at each position is calculated in real time, and the calculated temperature change rate is compared with a preset threshold to determine whether it exceeds the preset threshold. When making the flow rate variation determination, the flow rate data at each position is compared with the expected flow rate to calculate the flow rate variation, that is, the absolute value of the difference between the flow rate data at each position and the expected flow rate is calculated. The calculation result is compared with a preset flow rate variation threshold for determination. When the temperature change rate and / or the flow rate variation exceed the preset threshold, the temperature drop determination and / or the flow rate variation determination is activated, and an abnormal report is generated. The abnormal report includes information such as the abnormal position, time, type, and specific values. According to the abnormal report, by matching with the cooling scheme library, abnormal management is performed according to the matching result.

[0034] Furthermore, as Figure 2As shown, in the method provided by the application embodiment, the abnormal management according to the cooling control abnormality further includes: Establish a combined cooling solution library; perform adaptive matching of the combined cooling solution library according to the cooling control abnormality; and complete abnormal management based on the adaptive matching result.

[0035] In the embodiment of the present application, various different cooling solutions are obtained through the historical database. These solutions should cover various cooling strategies and methods, including forced convection cooling, natural convection cooling, spray cooling, water cooling, air cooling, etc. Each cooling solution is parametrically described, including but not limited to the type of cooling medium, the flow rate range of the cooling medium, the temperature range of the cooling medium, the applicable temperature drop rate, and the flow variation range. According to different cooling requirements and abnormal situations, the cooling solutions are classified and stored to complete the establishment of the combined cooling solution library.

[0036] Next, perform adaptive matching of the combined cooling solution library according to the cooling control abnormality. During the cooling process, detect abnormalities in real time, such as abnormal temperature drop rate and abnormal flow variation, and record the specific conditions of the abnormalities, including the type of abnormality, the occurrence location, time, and relevant parameters. Extract characteristic parameters from the recorded abnormal conditions, such as the temperature change rate at the abnormal location and the flow variation. Calculate the similarity between the abnormal characteristics and the cooling solution parameters, and select the solution with the highest similarity. According to the result of the matching algorithm, extract the cooling solution with the highest similarity from the solution library. According to the adaptive matching result, apply the selected cooling solution to the actual cooling process to complete abnormal management.

[0037] Furthermore, the method provided by the application embodiment further includes: Call the coolant data in the cooling control, and establish a usage database of the coolant based on the coolant data; perform state prediction based on the prediction network according to the usage database to generate a state prediction result; and perform coolant update processing according to the state prediction result.

[0038] In the embodiments of the present application, sensors are used to monitor relevant data of the coolant in real time. These data include, but are not limited to, the temperature, flow rate, pressure, component concentration, and usage time of the coolant. The collected coolant data is sorted and cleaned to remove outliers and noise data to ensure the quality of the data. A usage database of the coolant is established based on the processed coolant data. This database contains various usage information of the coolant, such as the start and end times of each use, the amount of coolant used, the environmental parameters during use, the replacement records of the coolant, etc. Before inputting the data into the prediction network, the data is preprocessed. The preprocessing includes steps such as data cleaning, data conversion, and data feature extraction. A prediction network is trained using the preprocessed coolant data. In the present application, a long short-term memory network is used for training. By training this prediction network, the future state of the coolant, such as the remaining service life, can be predicted based on real-time data. The real-time coolant data is input into the prediction network to generate a state prediction result. According to the state prediction result, a corresponding coolant update processing strategy is formulated. For example, if the prediction result shows that the remaining service life of the coolant is short, then the coolant is replaced to complete the coolant update process.

[0039] Further, the method provided by the application embodiments further includes: Extract cooling strategies for the first casting area and the second casting area, establish a sensitive window based on the cooling strategy extraction results; establish a high-frequency penalty factor in the sensitive window, and update the cooling control of the third casting area through the high-frequency penalty factor.

[0040] In the embodiments of the present application, first, sensors are used to collect temperature data, cooling medium flow rate data, etc. of the first casting area and the second casting area. According to the collected data, the cooling strategies of the first casting area and the second casting area are extracted from a preset cooling strategy database. Next, based on the cooling strategy extraction results, a time window sensitive to temperature changes is determined. In this process, by analyzing the temperature data, time periods with large temperature changes or significant cooling effects are identified. For example, when the temperature change rate exceeds 10 °C / minute, these time periods are determined as sensitive windows. Temperature data and cooling medium flow rate data are collected at high frequency within the sensitive window. For example, data is collected once per second. Then, a data processing tool is used for high-frequency data analysis to calculate the fluctuation amplitude and frequency. The high-frequency penalty factor is determined through a preset high-frequency penalty factor formula.

[0041] The high-frequency penalty factor formula is , where is the high-frequency penalty factor, and are adjustment coefficients, and these coefficients are determined by technical experts based on experimental data. is the temperature change rate, is the flow rate change rate.

[0042] Finally, update the cooling control of the third casting area according to the high-frequency penalty factor, and adjust the flow rate and temperature parameters of the cooling medium according to the value of the high-frequency penalty factor.

[0043] In the embodiments of the present application, in summary, the embodiments of the present application at least have the following technical effects: The present application divides the metal casting into casting areas, establishes a first casting area, a second casting area and a third casting area. Among them, the first casting area is a rapid cooling area, the second casting area is a slow cooling area, and the third casting area is the critical area between the first casting area and the second casting area; configure temperature monitoring sensors to monitor the temperatures of the first casting area and the second casting area, and establish a verification data set; obtain the material information of the metal casting, perform cooling prediction fitting on the first casting area and the second casting area according to the material information and the cooling medium information, and verify and update the cooling prediction fitting result through the verification data set to generate an updated cooling prediction fitting result; perform heat conduction analysis on the third casting area according to the updated cooling prediction fitting result, and establish a heat conduction influence fitting result of the third casting area; configure a cooling strategy for balancing the critical area through the heat conduction influence fitting result, and establish the flow rate parameter and temperature parameter of the cooling medium; perform cooling control on the third casting area according to the flow rate parameter and the temperature parameter. The present invention solves the technical problem that when the existing technology cools the casting, there is stress concentration in the critical area between the rapid cooling area and the slow cooling area, and the reliability and durability of the casting are low. By performing heat conduction analysis, configuring a balanced cooling strategy, and performing cooling control, the technical effect of improving the reliability and durability of the casting is achieved.

[0044] It should be noted that the above order of the embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above description of specific embodiments of this specification is given. The processes depicted in the drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0045] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0046] This specification and the drawings are only exemplary descriptions of the present application and are considered to have covered any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. A combined cooling control method for cooling metal castings, characterized in that: The method comprises: Partitioning the metal casting into casting zones to establish a first casting zone, a second casting zone and a third casting zone, wherein the first casting zone is a rapid cooling zone, the second casting zone is a slow cooling zone, and the third casting zone is a critical zone between the first casting zone and the second casting zone; configuring a temperature monitoring sensor to perform temperature monitoring of the first casting area and the second casting area, and establishing a verification data set; Acquire material information of the metal casting, perform cooling prediction fitting of the first casting area and the second casting area according to the material information and the cooling medium information, verify and update the cooling prediction fitting result through the verification data set, and generate an updated cooling prediction fitting result; Performing heat conduction analysis on the third casting region according to the updated cooling prediction fitting result, and establishing a heat conduction influence fitting result of the third casting region; The cooling strategy of the critical area of ​​the balance is configured by the heat conduction influence fitting result, and the flow parameters and temperature parameters of the cooling medium are established; Cooling control of the third casting area is performed according to the flow parameter and the temperature parameter.

2. The combined cooling control method for cooling metal castings according to claim 1, characterized in that: The cooling prediction fitting of the first casting area and the second casting area according to the material information and the cooling medium information also includes: The fitting formula is established as follows: ； in, Characterize the cooling prediction fitting results over time, is the initial temperature of the casting, is time, which is the independent variable in the formula and is used to track the change of temperature over time. is the thermal diffusivity, is the Laplace operator of temperature, is the heat exchange coefficient, is the specific heat capacity, is the flow rate of cooling medium, is the temperature of the cooling medium, is the environmental impact function, which is used to describe the impact of ambient temperature on system temperature; Cooling prediction fitting of the first casting region and the second casting region is performed according to the fitting formula.

3. The combined cooling control method for cooling metal castings according to claim 2, characterized in that: The step of performing heat conduction analysis on the third casting region according to the updated cooling prediction fitting result and establishing a heat conduction influence fitting result of the third casting region further includes: The position heat conduction formula is established as follows: ； in, Characterizes the location of the third casting area The rate of change of temperature with time, For location The thermal diffusivity at For location The second-order derivative of temperature space at , For location The heat transfer coefficient at and The third interval area location The weight coefficient of the influence of the first casting area and the second casting area, Updated cooling prediction fit results for the first casting region, Updated cooling prediction fit results for the second casting region, The third casting area location In time Temperature; The heat conduction influence fitting result is established according to the position heat conduction formula.

4. The combined cooling control method for cooling metal castings according to claim 3, characterized in that: The cooling strategy of the critical area of ​​the balance is configured by the heat conduction influence fitting result, and the flow parameters and temperature parameters of the cooling medium are established, and further includes: Configure the flow parameter adjustment formula and temperature parameter adjustment formula of the cooling medium as follows: ； ； in, The third interval area location In time The cooling medium flow rate, For location The baseline flow rate at For location The flow regulation coefficient at For location In time The cooling medium temperature, For location The baseline temperature at For location Temperature regulation coefficient at The flow parameter and temperature parameter of the cooling medium are established according to the flow parameter adjustment formula and the temperature parameter adjustment formula.

5. The combined cooling control method for cooling metal castings according to claim 1, characterized in that: The method further comprises: Performing control monitoring on the cooling control and establishing a monitoring data set; Performing trigger determination based on the monitoring data set, wherein the trigger determination includes temperature drop rate determination and flow rate variation determination; If the temperature drop determination and / or the flow rate variation determination is activated, a cooling control abnormality is reported, and abnormality management is performed based on the cooling control abnormality.

6. The combined cooling control method for cooling metal castings according to claim 5, characterized in that: The performing abnormality management according to the cooling control abnormality includes: Establish a library of combined cooling solutions; Execute adaptation and matching of the combined cooling solution library according to the cooling control anomaly; Complete exception management based on the adaptation and matching results.

7. The combined cooling control method for cooling metal castings according to claim 1, characterized in that: The method further comprises: Calling coolant data in cooling control, and establishing a coolant usage database based on the coolant data; Performing a state prediction based on a prediction network according to the usage database to generate a state prediction result; The coolant is updated according to the state prediction result.

8. The combined cooling control method for cooling metal castings according to claim 1, characterized in that: The method further comprises: Extracting cooling strategies for the first casting area and the second casting area, and establishing a sensitive window based on the cooling strategy extraction results; A high frequency penalty factor is established in the sensitive window, and cooling control of the third casting region is updated by the high frequency penalty factor.

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