Partition cooling regulation and control system and method for injection mold temperature field coupling simulation

Abstract

The invention discloses a partition cooling regulation and control system and method for injection mold temperature field coupling simulation, and relates to the technical field of temperature field coupling simulation, and the method comprises the steps: obtaining environment data at the position of an injection mold, and constructing a digital twin model at the position of the injection mold based on the environment data at the position of the injection mold; analyzing the structural complexity of the position of the injection mold; determining the temperature complexity of each area at the position of the injection mold; comprehensively evaluating the cooling regulation and control precision of the position of the injection mold by combining the structural complexity of the position of the injection mold and the temperature complexity of each area of the position of the injection mold; and based on the cooling regulation and control precision of all the areas of the injection mold position, subarea cooling regulation and control are conducted on the injection mold position. The method has the beneficial effects that dynamic regulation and control precision setting of the injection mold is achieved, differential regulation and control areas are intelligently divided, the temperature control precision of a high-fluctuation area is remarkably improved, and meanwhile waste of cooling resources is effectively reduced.

Description

Technical Field

[0001] This invention relates to the field of temperature field coupling simulation technology, specifically to a zoned cooling control system and method for temperature field coupling simulation of injection molds. Background Technology

[0002] In plastic injection molding, precise control of the mold temperature field is crucial for product quality, molding cycle, and energy consumption. However, current mold temperature control generally adopts a uniform control strategy across the entire mold cavity, applying fixed cooling parameters. This strategy ignores the significant spatial differences in the mold's internal structure and temperature distribution: areas with high heat accumulation experience drastic temperature fluctuations, requiring intensive cooling to ensure control accuracy, while areas with stable temperatures can be adequately cooled with low-intensity cooling. This traditional "one-size-fits-all" approach not only wastes cooling resources but also leads to product defects due to insufficient cooling in high-demand areas, making it difficult to meet the requirements of precision injection molding. Especially in advanced processes such as complex mold structures and multi-material co-injection, the rigidity of uniform control further amplifies the impact of uneven temperature distribution on product quality. Summary of the Invention

[0003] To solve the above-mentioned technical problems, a zoned cooling control system and method for coupled simulation of temperature field in injection molds is provided. This technical solution solves at least one of the problems mentioned in the background art.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0005] A method for zoned cooling control based on coupled simulation of temperature field in injection molds includes:

[0006] Obtain environmental data at the injection mold location, and construct a digital twin model of the injection mold location based on the environmental data.

[0007] Based on the digital twin model of the injection mold location, the structural complexity of the injection mold location is analyzed;

[0008] Temperature field simulation tests were conducted at the injection mold location to determine the temperature complexity of each region at the injection mold location.

[0009] The accuracy of cooling control at the injection mold location is comprehensively evaluated by combining the structural complexity at the injection mold location and the temperature complexity of each area at the injection mold location.

[0010] Based on the cooling control precision of each area at the injection mold location, zoned cooling control is implemented at the injection mold location.

[0011] As a preferred embodiment of the present invention, the structural complexity at the injection mold location is analyzed based on a digital twin model of the injection mold location using the following method and steps:

[0012] Based on the types of physical models in the digital twin model at the injection mold location, spatial regions are divided into types, with areas requiring cooling designated as cooling regions and areas that do not require cooling but are affected by heat as heat-affected regions.

[0013] Determine the number of cooling channels per square meter within the cooling area, and denot this as the cooling channel density;

[0014] Determine the proportion of space occupied by the heat-affected zone at the injection mold location, and denot it as the heat-affected volume percentage.

[0015] The structural complexity at the injection mold location is comprehensively evaluated by combining the density of cooling channels and the proportion of heat-affected volume.

[0016] More specifically, the structural complexity is calculated using the following formula:

[0017] ;

[0018] Where SCI represents the structural complexity at the injection mold location, CD represents the cooling channel density, HP represents the heat-affected zone volume ratio, and α and β represent the contribution weights, with α + β = 1. The values ​​of α and β are set based on the actual structure. When the cooling channel distribution is relatively uniform throughout the entire area, the contribution weight of the cooling channel density should be reduced. Similarly, when the heat-affected zone distribution is relatively uniform, the contribution weight of the heat-affected zone volume ratio should be reduced. The density index of cooling channels. This is the thermal effect ratio index.

[0019] As a preferred embodiment of the present invention, the step of conducting a temperature field simulation test at the injection mold location to determine the temperature complexity of each region at the injection mold location specifically includes:

[0020] Obtain the maximum simulation accuracy of the simulation software, and based on the maximum simulation accuracy of the simulation software, divide the digital twin model at the injection mold location into several minimum simulation regions;

[0021] Based on the production plan, a simulation cycle is set. Within the simulation cycle, the simulation software is used to perform continuous temperature simulation of each simulation area at its maximum simulation accuracy to obtain the temperature simulation curve of each simulation area.

[0022] Based on the temperature simulation curves of all simulation regions, the auto-temperature variation complexity and the ring-temperature variation complexity of each simulation region are determined respectively. The auto-temperature variation complexity is the minimum time interval during which the fluctuation value of the temperature simulation curve of the simulation region is greater than the fluctuation threshold, and the ring-temperature variation complexity is the absolute difference between the temperature simulation curves of the simulation region and other simulation regions.

[0023] As a preferred embodiment of the present invention, the comprehensive evaluation of the cooling control accuracy at the injection mold location, combining the structural complexity at the injection mold location and the temperature complexity of each region at the injection mold location, specifically includes:

[0024] Based on the structural complexity at the injection mold location and combined with historical simulation data, the baseline cooling parameters for the injection mold location are determined.

[0025] Based on the complexity of the ring-ratio temperature change in each simulation region, the injection mold position is divided into several control regions. The cooling control resolution of the control region is defined as the size of the divided region being smaller than or equal to that of the control region.

[0026] The control time interval for each control region is determined based on the self-comparison temperature change complexity of each simulation region.

[0027] As a preferred embodiment of the present invention, the criteria for dividing the control region are as follows:

[0028] The control region consists of several consecutive adjacent simulation regions;

[0029] The complexity of the ring-ratio temperature change between any two simulated regions within each control region is less than the threshold.

[0030] If there is no adjacent simulation region whose temperature variation complexity is less than the threshold, then the simulation region is used as the control region alone.

[0031] As a preferred embodiment of the present invention, the determination of the control time interval for each control region based on the self-comparison temperature change complexity of each simulation region specifically includes:

[0032] The auto-temperature variation complexity of all simulated regions included in the control area is collected, and the minimum value is determined as the fluctuation time interval of the control area.

[0033] Half of the fluctuation time interval of the control area is taken as the control time interval of the control area.

[0034] As a preferred embodiment of the present invention, the zonal cooling control at the injection mold location based on the cooling control accuracy of each region at the injection mold location specifically includes:

[0035] A baseline cooling parameter is used to perform global baseline cooling control at the injection mold location, and global temperature data is obtained.

[0036] On the basis of ensuring that the control time points of any two different control regions are different, and that the interval between two adjacent control time points of the same control region is less than the control time interval of that control region, a control time is set for each control region.

[0037] At the control moment, the control resolution of the cooling system is adjusted to be greater than or equal to the control accuracy of the control area, and centralized cooling control is performed on the control area to obtain the control temperature data of the area.

[0038] Furthermore, a zoned cooling control system for coupled simulation of the temperature field in injection molds is proposed, comprising:

[0039] A cooling system, wherein the cooling system supports adjustment of cooling parameters;

[0040] The control module is connected to the cooling system. The control module outputs control signals to the cooling system according to the partitioned cooling control method of injection mold temperature field coupling simulation as described above, and controls the cooling system to adjust parameters.

[0041] The control module includes:

[0042] A storage unit, wherein the storage unit stores a control program, which, when invoked, executes the partitioned cooling control method of the injection mold temperature field coupling simulation as described above.

[0043] A central processing unit (CPU) coupled to the storage unit, the CPU being used to call a control program to generate cooling system control signals;

[0044] A communication port, which is used to transmit cooling system control signals to the cooling system;

[0045] A temperature field simulation module is connected to the cooling system. The temperature field simulation module is used to reconstruct the temperature field at the injection mold location based on the global temperature data and regional control temperature data collected by the cooling system.

[0046] The temperature field simulation module specifically includes:

[0047] A basic temperature field construction unit is used to construct a basic temperature field at the injection mold location based on global temperature data.

[0048] The temperature field calibration and reconstruction unit is used to reconstruct and replace the corresponding area position in the basic temperature field based on the regional control temperature data of each control area collected, so as to obtain the reconstructed temperature field at the injection mold position.

[0049] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0050] This invention proposes a dynamic coupling analysis of structural complexity and temperature fluctuation characteristics, effectively addressing the limitations of traditional control methods. Based on adaptive evaluation of mold structural characteristics and regional temperature variation patterns, the system can intelligently divide differentiated control regions and dynamically adjust the parameters and control frequency of the cooling system. This significantly improves temperature control accuracy in high-fluctuation regions and reduces redundant operations in low-fluctuation regions. Simultaneously, through a collaborative reconstruction mechanism of global baseline data and local high-precision control, combined with spatial mapping of a digital twin model, the temperature gradient distribution in the core region can be accurately reconstructed, overcoming the accuracy deficiencies of traditional control algorithms. This method not only improves the reliability of temperature control under complex mold structures but also provides high-precision data support for process optimization and product quality improvement, demonstrating significant engineering application value. Attached Figure Description

[0051] Figure 1 This is a flowchart of the zoned cooling control method for coupled simulation of the temperature field of injection mold proposed in Embodiment 1 of this scheme;

[0052] Figure 2 This is a flowchart of the method for analyzing the structural complexity at the injection mold location proposed in Embodiment 2 of this scheme;

[0053] Figure 3 This is a flowchart of the method for determining the temperature complexity of each region at the injection mold location, as proposed in Embodiment 3 of this scheme;

[0054] Figure 4 This is a flowchart of the method for comprehensively evaluating the cooling control accuracy at the injection mold location, as proposed in Embodiment 3 of this scheme;

[0055] Figure 5 This is a flowchart of the method for zoned cooling control at the injection mold location proposed in Embodiment 3 of this scheme. Detailed Implementation

[0056] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0057] Example 1:

[0058] Reference Figure 1As shown, the zoned cooling control method for coupled simulation of injection mold temperature field in this embodiment includes:

[0059] Obtain environmental data at the injection mold location, and construct a digital twin model of the injection mold location based on the environmental data.

[0060] Digital twin models transform the physical environment into a virtual digital model, enabling precise replication of the complex structure of injection molds. These models integrate multi-source environmental data (such as mold structure, cooling channel layout, and heat-affected zones), providing a high-fidelity virtual experimental platform for subsequent analysis. This avoids the simplification errors of traditional empirical formulas for complex structures and improves the structural adaptability of control methods.

[0061] Based on the digital twin model of the injection mold location, the structural complexity of the injection mold location is analyzed;

[0062] By leveraging the spatial analytical capabilities of digital twin models, structural parameters such as cooling channel density and heat-affected volume ratio are quantified, transforming abstract "complexity" into a calculable index system. This method can accurately identify the structural characteristics and heat-affected volume intensity of different regions, providing a scientific basis for the differentiated design of control strategies and significantly improving the adaptability of control precision to structural heterogeneity.

[0063] Temperature field simulation tests were conducted at the injection mold location to determine the temperature complexity of each region at the injection mold location.

[0064] By acquiring the spatiotemporal evolution characteristics of the temperature field through dynamic simulation experiments and extracting dynamic indicators such as the complexity of auto- and cyclic temperature changes, this method overcomes the limitations of traditional static analysis methods. This approach can capture complex phenomena such as local high-temperature accumulation and thermal coupling effects, providing accurate temperature characteristic descriptions for regional assessment of control precision and ensuring a high degree of matching between control strategies and actual operating conditions.

[0065] The accuracy of cooling control at the injection mold location is comprehensively evaluated by combining the structural complexity at the injection mold location and the temperature complexity of each area at the injection mold location.

[0066] A joint evaluation mechanism for structural complexity and temperature complexity is established, organically combining static structural factors with dynamic temperature characteristics to form a multi-dimensional control accuracy evaluation system. This method can comprehensively consider the coupling effect of thermal influence, cooling channel distribution, and temperature fluctuations, avoiding control deviations caused by a single factor and significantly improving the reliability and stability of control accuracy.

[0067] Based on the cooling control precision of each area at the injection mold location, zoned cooling control is implemented at the injection mold location.

[0068] By employing a regionalized control strategy, the parameters and control frequency of the cooling system are dynamically adjusted to meet the cooling control precision requirements of different regions, achieving "regional customized control." This method effectively solves the problem of insufficient local precision caused by traditional global unified control, significantly improves the spatial resolution and temporal consistency of temperature field control, and meets the high-precision temperature control requirements in injection mold scenarios.

[0069] Example 2:

[0070] In this embodiment, refer to Figure 2 As shown, based on the digital twin model of the injection mold location, the structural complexity at the injection mold location is analyzed using the following steps:

[0071] Based on the types of physical models in the digital twin model at the injection mold location, spatial regions are divided into types, with areas requiring cooling designated as cooling regions and areas that do not require cooling but are affected by heat as heat-affected regions.

[0072] Determine the number of cooling channels per square meter within the cooling area, and denot this as the cooling channel density;

[0073] Determine the proportion of space occupied by the heat-affected zone at the injection mold location, and denot it as the heat-affected volume percentage.

[0074] The structural complexity at the injection mold location is comprehensively evaluated by combining the density of cooling channels and the proportion of heat-affected volume.

[0075] More specifically, the structural complexity is calculated using the following formula:

[0076] ;

[0077] Where SCI represents the structural complexity at the injection mold location, CD represents the cooling channel density, HP represents the heat-affected zone volume ratio, and α and β represent the contribution weights, with α + β = 1. The values ​​of α and β are set based on the actual structure. When the cooling channel distribution is relatively uniform throughout the entire area, the contribution weight of the cooling channel density should be reduced. Similarly, when the heat-affected zone distribution is relatively uniform, the contribution weight of the heat-affected zone volume ratio should be reduced. The density index of cooling channels. The thermal effect ratio index;

[0078] in, and All are less than 1. Specifically, in some preferred embodiments, τ1=0.6 and τ2=0.4. The reasons for the values ​​in the preferred embodiments are explained in detail below with examples.

[0079] Since the structural complexity in this scheme is calculated by weighted summation of cooling channel density and heat-affected volume ratio at the injection mold location, if only linear relationship fitting is used, the complexity of high-density scenarios and heat-affected volume ratio will be excessively amplified. In reality, as the cooling channel density and heat-affected volume ratio increase, the contribution of each additional target will gradually decrease. Therefore, cooling channel density index and heat-affected volume ratio index less than 1 are used to simulate diminishing marginal effects.

[0080] Specifically, regarding cooling channel density, in practical applications, the cooling channel density at the injection mold location is usually concentrated in the range of 0.1-1.5. In this case, a cooling channel density index of 0.6 can more accurately reflect the contribution of cooling channel density to complexity. For example, 0.1^0.6≈0.25, 1^0.6=1, 1.5^0.6≈1.27. However, when the cooling channel density index is 0.4, 0.1^0.4≈0.40, 1^0.5=1, 1.5^0.4≈1.17. At this time, it is difficult to accurately reflect the contribution of cooling channel density changes to complexity. Based on this, after multiple empirical investigations, it was determined that a cooling channel density index of 0.6 is the optimal value. Similarly, the heat-affected zone ratio index of 0.4 in the preferred embodiment is also an empirical value obtained through multiple practical investigations.

[0081] In this embodiment, the correspondence between the SCI calculated above and the selected reference cooling parameters is as follows:

[0082] When the SCI is between 0 and 2, the reference cooling flow rate is 50% of the standard flow rate; when the SCI is between 3 and 5, the reference cooling flow rate is 80% of the standard flow rate.

[0083] Example 3:

[0084] In this embodiment, refer to Figure 3 As shown, a temperature field simulation experiment was conducted at the injection mold location to determine the specific temperature complexity of each region at the injection mold location, including:

[0085] Obtain the maximum simulation accuracy of the simulation software, and based on the maximum simulation accuracy of the simulation software, divide the digital twin model at the injection mold location into several minimum simulation regions;

[0086] Based on the performance of the simulation software, the injection mold location is divided into regions. The simulation unit corresponding to the resolution of the maximum simulation accuracy is taken as the minimum simulation region. This minimum simulation region represents the highest simulation accuracy. In the actual simulation process, this minimum simulation region is the smallest region that can be accurately simulated based on the algorithm limitations of the simulation software.

[0087] Based on the production plan, a simulation cycle is set. Within the simulation cycle, the simulation software is used to perform continuous temperature simulation of each simulation area at its maximum simulation accuracy to obtain the temperature simulation curve of each simulation area.

[0088] Based on the temperature simulation curves of all simulation regions, the auto-temperature variation complexity and the ring-temperature variation complexity of each simulation region are determined. The auto-temperature variation complexity is the minimum time interval during which the fluctuation value of the temperature simulation curve of the simulation region exceeds the fluctuation threshold, and the ring-temperature variation complexity is the absolute difference between the temperature simulation curves of the simulation region and other simulation regions.

[0089] Reference Figure 4 As shown, considering both the structural complexity and the temperature complexity of different areas at the injection mold location, the specific evaluation of the cooling control precision at the injection mold location is as follows:

[0090] Based on the structural complexity at the injection mold location and combined with historical simulation data, the baseline cooling parameters for the injection mold location are determined.

[0091] Based on the complexity of the ring-ratio temperature change in each simulation region, the injection mold position is divided into several control regions. The cooling control resolution of the control region is defined as the size of the divided region being smaller than or equal to that of the control region.

[0092] The criteria for dividing the control area are as follows:

[0093] The control region consists of several consecutive adjacent simulation regions;

[0094] The complexity of the ring-ratio temperature change between any two simulated regions within each control region is less than the threshold.

[0095] If there is no adjacent simulation region whose temperature variation complexity is less than the threshold, then the simulation region is used as the control region alone.

[0096] When the regional temperatures are similar, a unified temperature control of the entire region can achieve an effective temperature control effect. In this embodiment, by integrating regions with similar temperatures into separate control regions, intelligent division of differentiated control regions is achieved.

[0097] The auto-temperature variation complexity of all simulated regions included in the control area is collected, and the minimum value is determined as the fluctuation time interval of the control area.

[0098] Half of the fluctuation time interval of the control area is taken as the control time interval of the control area.

[0099] By analyzing the frequency of temperature fluctuations, dynamic control of high-fluctuation and low-change regions was achieved. High-frequency control operations were performed in high-fluctuation regions, while redundant control operations in low-change regions were reduced.

[0100] In this embodiment: Refer to Figure 5 As shown, the specific steps for zoned cooling control at the injection mold location, based on the cooling control precision of each area, are as follows:

[0101] A baseline cooling parameter is used to perform global baseline cooling control at the injection mold location, and global temperature data is obtained.

[0102] On the basis of ensuring that the control time points of any two different control regions are different, and that the interval between two adjacent control time points of the same control region is less than the control time interval of that control region, a control time is set for each control region.

[0103] At the control moment, the control resolution of the cooling system is adjusted to be greater than or equal to the control accuracy of the control area, and centralized cooling control is performed on the control area to obtain the control temperature data of the area.

[0104] By intelligently dividing the differential control zones and dynamically adjusting the parameters and control frequency of the cooling system, the temperature control accuracy in high-fluctuation zones is significantly improved, while redundant operations in low-change zones are reduced, thus achieving reliable temperature control under complex mold structures.

[0105] Example 4:

[0106] This embodiment, combining the zoned cooling control method for coupled simulation of injection mold temperature field proposed in embodiments one to three above, proposes a zoned cooling control system for coupled simulation of injection mold temperature field, including:

[0107] The cooling system supports adjustment of cooling parameters;

[0108] The control module is connected to the cooling system. The control module outputs control signals to the cooling system according to the zoned cooling control method of injection mold temperature field coupling simulation as described above, and controls the cooling system to adjust parameters.

[0109] The temperature field simulation module is connected to the cooling system. It is used to reconstruct the temperature field at the injection mold location based on the global temperature data and regional control temperature data collected by the cooling system.

[0110] The control module includes:

[0111] The storage unit stores the control program, which, when invoked, executes the partitioned cooling control method described above for the coupled simulation of the temperature field of the injection mold.

[0112] The central processing unit (CPU) is coupled to the storage unit. The CPU is used to call the control program to generate control signals for the cooling system.

[0113] The communication port is used to transmit cooling system control signals to the cooling system.

[0114] The temperature field simulation module specifically includes:

[0115] The basic temperature field construction unit is used to construct the basic temperature field at the injection mold location based on global temperature data.

[0116] The temperature field calibration and reconstruction unit is used to reconstruct and replace the corresponding area position in the basic temperature field based on the regional control temperature data of each control area collected, so as to obtain the reconstructed temperature field at the injection mold position. The temperature during the control interval of the control area is determined by interpolation calculation.

[0117] By employing a collaborative reconstruction mechanism combining global baseline data and local high-precision control, and integrating spatial mapping with a digital twin model, the temperature gradient distribution in the core region can be accurately reconstructed, overcoming the accuracy deficiencies of traditional control algorithms. This method not only improves the reliability of temperature control under complex mold structures but also provides high-precision data support for process optimization and product quality improvement, demonstrating significant engineering application value.

[0118] In summary, the advantages of this invention are: by dynamically coupling analysis of structural complexity and temperature fluctuation characteristics, the dynamic control precision setting of injection mold is realized, the differentiated control area is intelligently divided, and the parameters and control frequency of the cooling system are dynamically adjusted, which not only significantly improves the temperature control precision in the high fluctuation area, but also effectively reduces the waste of cooling resources.

[0119] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A method for zoned cooling control based on coupled simulation of temperature field in injection molds, characterized in that, include: Obtain environmental data at the injection mold location, and construct a digital twin model of the injection mold location based on the environmental data. Based on the digital twin model of the injection mold location, the structural complexity of the injection mold location is analyzed; Temperature field simulation tests were conducted at the injection mold location to determine the temperature complexity of each region at the injection mold location. The accuracy of cooling control at the injection mold location is comprehensively evaluated by combining the structural complexity at the injection mold location and the temperature complexity of each area at the injection mold location. Based on the cooling control precision of each area at the injection mold location, zoned cooling control is implemented at the injection mold location.

2. The zoned cooling control method for coupled simulation of injection mold temperature field according to claim 1, characterized in that, The analysis of the structural complexity at the injection mold location based on the digital twin model specifically includes: Based on the types of physical models in the digital twin model at the injection mold location, spatial regions are divided into types, with areas requiring cooling designated as cooling regions and areas that do not require cooling but are affected by heat as heat-affected regions. Determine the number of cooling channels per square meter within the cooling area, and denot this as the cooling channel density; Determine the proportion of space occupied by the heat-affected zone at the injection mold location, and denot it as the heat-affected volume percentage. The structural complexity at the injection mold location is comprehensively evaluated by combining the density of cooling channels and the proportion of heat-affected volume.

3. The zoned cooling control method for coupled simulation of injection mold temperature field according to claim 2, characterized in that, The temperature field simulation test at the injection mold location, to determine the temperature complexity of each region at the injection mold location, specifically includes: Obtain the maximum simulation accuracy of the simulation software, and based on the maximum simulation accuracy of the simulation software, divide the digital twin model at the injection mold location into several minimum simulation regions; Based on the production plan, a simulation cycle is set. Within the simulation cycle, the simulation software is used to perform continuous temperature simulation of each simulation area at its maximum simulation accuracy to obtain the temperature simulation curve of each simulation area. Based on the temperature simulation curves of all simulation regions, the auto-temperature variation complexity and the ring-temperature variation complexity of each simulation region are determined respectively. The auto-temperature variation complexity is the minimum time interval during which the fluctuation value of the temperature simulation curve of the simulation region is greater than the fluctuation threshold, and the ring-temperature variation complexity is the absolute difference between the temperature simulation curves of the simulation region and other simulation regions.

4. The zoned cooling control method for coupled simulation of injection mold temperature field according to claim 3, characterized in that, The comprehensive evaluation of the cooling control accuracy at the injection mold location, combining the structural complexity of the injection mold location with the temperature complexity of various regions at the injection mold location, specifically includes: Based on the structural complexity at the injection mold location and combined with historical simulation data, the baseline cooling parameters for the injection mold location are determined. Based on the complexity of the ring-ratio temperature change in each simulation region, the injection mold position is divided into several control regions. The cooling control resolution of the control region is defined as the size of the divided region being smaller than or equal to that of the control region. The control time interval for each control region is determined based on the self-comparison temperature change complexity of each simulation region.

5. The zoned cooling control method for coupled simulation of injection mold temperature field according to claim 4, characterized in that, The criteria for dividing the control region are as follows: The control region consists of several consecutive adjacent simulation regions; The complexity of the ring-ratio temperature change between any two simulated regions within each control region is less than the threshold. If there is no adjacent simulation region whose temperature variation complexity is less than the threshold, then the simulation region is used as the control region alone.

6. The zoned cooling control method for coupled simulation of injection mold temperature field according to claim 5, characterized in that, The determination of the control time interval for each control region based on the self-comparison temperature change complexity of each simulation region specifically includes: The auto-temperature variation complexity of all simulated regions included in the control area is collected, and the minimum value is determined as the fluctuation time interval of the control area. Half of the fluctuation time interval of the control area is taken as the control time interval of the control area.

7. The zoned cooling control method for coupled simulation of injection mold temperature field according to claim 6, characterized in that, The specific implementation of zoned cooling control at the injection mold location based on the cooling control accuracy of each region at the injection mold location includes: A baseline cooling parameter is used to perform global baseline cooling control at the injection mold location, and global temperature data is obtained. On the basis of ensuring that the control time points of any two different control regions are different, and that the interval between two adjacent control time points of the same control region is less than the control time interval of that control region, a control time is set for each control region. At the control moment, the control resolution of the cooling system is adjusted to be greater than or equal to the control accuracy of the control area, and centralized cooling control is performed on the control area to obtain the control temperature data of the area.

8. A zoned cooling control system for coupled simulation of temperature field in injection molds, characterized in that, include: A cooling system, wherein the cooling system supports adjustment of cooling parameters; The control module is connected to the cooling system. The control module outputs a control signal to the cooling system according to the partitioned cooling control method of injection mold temperature field coupling simulation as described in any one of claims 1-7, and controls the cooling system to adjust parameters. A temperature field simulation module is connected to the cooling system. The temperature field simulation module is used to reconstruct the temperature field at the injection mold location based on the global temperature data and regional control temperature data collected by the cooling system.

9. A zoned cooling control system for coupled simulation of temperature field in injection molds according to claim 8, characterized in that, The control module includes: A storage unit, wherein the storage unit stores a control program, and when the control program is invoked, it executes the partitioned cooling control method for coupling simulation of injection mold temperature field as described in any one of claims 1-7. A central processing unit (CPU) coupled to the storage unit, the CPU being used to call a control program to generate cooling system control signals; A communication port is used to transmit cooling system control signals to the cooling system.

10. A zoned cooling control system for coupled simulation of temperature field in injection molds according to claim 8, characterized in that, The temperature field simulation module specifically includes: A basic temperature field construction unit is used to construct a basic temperature field at the injection mold location based on global temperature data. The temperature field calibration and reconstruction unit is used to reconstruct and replace the corresponding area position in the basic temperature field based on the regional control temperature data of each control area collected, so as to obtain the reconstructed temperature field at the injection mold position.

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