A cooling control method and system for plastic injection molds

Abstract

This invention discloses a cooling control method and system for plastic injection molds, applied in the field of data processing technology. The method includes: acquiring the structure of a target plastic injection mold, obtained through three-dimensional image acquisition using an industrial CCD; injecting plastic material according to the target injection mold structure to determine injection temperature data; using the injection temperature data as index data to traverse a cooling control database and obtain N cooling schemes, where N is a positive integer greater than 1; performing a fitness analysis between the N cooling schemes and the target injection mold; optimizing the cooling control processing based on the fitness results to determine the cooling control processing result; and performing cooling control on the target plastic injection mold based on the cooling control processing result. This solves the technical problem in existing injection mold cooling control methods where low cooling control accuracy leads to poor stability of injection molded product quality.

Description

Technical Field

[0001] This invention relates to the field of data processing, and in particular to a cooling control method and system for plastic injection molds. Background Technology

[0002] Injection molding is a molding method for injection parts. During injection molding, because the raw material is a high-temperature plastic, the mold needs to be cooled. However, current technologies mostly use fixed parameter control for mold cooling, resulting in low precision and inconsistent product quality.

[0003] Therefore, the existing technology for cooling control of injection molds suffers from low cooling control precision, resulting in poor quality stability of injection molded products. Summary of the Invention

[0004] This application provides a cooling control method and system for plastic injection molds, which solves the technical problem that the cooling control accuracy of injection molds in the prior art is low, resulting in poor quality stability of injection molded products.

[0005] This application provides a cooling control method for plastic injection molds. The method includes: acquiring the structure of a target plastic injection mold, wherein the target plastic injection mold structure is obtained through three-dimensional image acquisition using an industrial CCD; injecting plastic material according to the target injection mold structure to determine injection temperature data; using the injection temperature data as index data, traversing a cooling control database to obtain N cooling schemes, where N is a positive integer greater than 1; performing a fitness analysis between the N cooling schemes and the target injection mold, optimizing the cooling control processing based on the fitness results, and determining the cooling control processing result; and performing cooling control on the target plastic injection mold based on the cooling control processing result.

[0006] This application also provides a cooling control system for a plastic injection mold. The system includes: a structure acquisition module for acquiring the structure of a target plastic injection mold, wherein the target plastic injection mold structure is obtained through three-dimensional image acquisition using an industrial CCD; a temperature data acquisition module for injecting plastic material according to the target injection mold structure and determining injection temperature data; a cooling scheme acquisition module for using the injection temperature data as index data to traverse a cooling control database and acquire N cooling schemes, where N is a positive integer greater than 1; a control optimization module for performing fitness analysis based on the N cooling schemes and the target injection mold, optimizing the cooling control processing based on the fitness results, and determining the cooling control processing result; and a cooling control module for performing cooling control on the target plastic injection mold based on the cooling control processing result.

[0007] This application also provides an electronic device, including:

[0008] Memory, used to store executable instructions;

[0009] The processor, when executing executable instructions stored in the memory, implements the cooling control method for a plastic injection mold provided in this application.

[0010] This application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements a cooling control method for a plastic injection mold provided in this application.

[0011] This application proposes a cooling control method and system for plastic injection molds. The method involves acquiring the target plastic injection mold structure, obtained through 3D image acquisition using an industrial CCD. Plastic material is injected based on the target injection mold structure to determine the injection temperature. This injection temperature data is used as index data to traverse a cooling control database, acquiring N cooling schemes, where N is a positive integer greater than 1. A fitness analysis is performed between these N cooling schemes and the target injection mold. Based on the fitness results, the cooling control process is optimized to determine the final cooling control result. Cooling control is then applied to the target plastic injection mold based on this result. This method achieves intelligent acquisition of cooling control methods for injection molds, improving the accuracy of cooling control and enhancing the stability of injection molded product quality. It solves the technical problem of low cooling control accuracy in existing injection mold cooling control methods, which leads to poor quality stability of injection molded products.

[0012] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below. Attached Figure Description

[0013] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings of the embodiments of this disclosure will be briefly described below. Obviously, the drawings described below only relate to some embodiments of this disclosure and are not intended to limit this disclosure.

[0014] Figure 1 A schematic flowchart illustrating a cooling control method for a plastic injection mold provided in this application embodiment;

[0015] Figure 2 A schematic flowchart illustrating the construction of a cooling control database for a cooling control method of a plastic injection mold provided in this application embodiment;

[0016] Figure 3 A flowchart illustrating the process of obtaining N cooling schemes for a cooling control method of a plastic injection mold provided in an embodiment of this application;

[0017] Figure 4 A schematic diagram of the system structure of a cooling control method for a plastic injection mold provided in this application embodiment;

[0018] Figure 5 This is a schematic diagram of the system electronic device for a cooling control method of a plastic injection mold provided in an embodiment of the present invention.

[0019] Explanation of reference numerals in the attached drawings: Structure acquisition module 11, Temperature data acquisition module 12, Cooling scheme acquisition module 13, Control optimization module 14, Cooling control module 15, Processor 31, Memory 32, Input device 33, Output device 34. Detailed Implementation

[0020] Example 1

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0023] In the following description, the terms "first, second, third" are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0024] 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 application belongs. The terminology used herein is for the purpose of describing embodiments of this application only.

[0025] While this application makes various references to certain modules of the system according to embodiments of this application, any number of different modules may be used and run on user terminals and / or servers. These modules are merely illustrative, and different aspects of the system and method may use different modules.

[0026] This application uses flowcharts to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, various steps can be processed in reverse order or simultaneously, as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0027] like Figure 1 As shown in the figure, this application embodiment provides a cooling control method for a plastic injection mold, the method comprising:

[0028] The target plastic injection mold structure is obtained by acquiring a three-dimensional image using an industrial CCD.

[0029] Based on the target injection mold structure, plastic material is injected, and injection temperature data is determined.

[0030] Using the injected temperature data as index data, the cooling control database is traversed to obtain N cooling schemes, where N is a positive integer greater than 1;

[0031] Injection molding is a molding method for injection-molded parts. During injection molding, because the raw material is a high-temperature plastic product, the injection mold needs to be cooled. However, in existing technologies, the cooling control methods for injection molds are mostly fixed parameter controls, with low intelligence, resulting in low cooling control accuracy and poor product quality stability. This paper addresses this issue by acquiring the target plastic injection mold structure, obtained through 3D image acquisition using an industrial CCD. Then, plastic material is injected based on the target injection mold structure to determine the injection temperature data, which is acquired using a temperature sensor on the injection equipment. Further, the injection temperature data is used as index data to traverse a cooling control database, obtaining N cooling schemes, where N is a positive integer greater than 1. In other words, the injection temperature data is used as index data to traverse the cooling control database and obtain N cooling schemes corresponding to the injection temperature data, where N is a positive integer greater than 1, and N represents the number of cooling schemes obtained.

[0032] like Figure 2 As shown, the method provided in this application embodiment further includes:

[0033] Cooling control parameters of the target plastic injection mold are collected based on big data.

[0034] Based on the cooling control parameters, analyze the cooling performance parameters and cooling rate parameters to determine the cooling performance characteristics and cooling rate characteristics;

[0035] The cooling performance characteristics and the cooling rate characteristics are correlated and mapped to construct a correlation mapping factor;

[0036] A cooling control database is constructed based on the aforementioned correlation mapping factors.

[0037] When constructing the cooling control database, cooling control parameters of the target plastic injection mold are collected through big data analysis. These parameters include the corresponding cooling effects. Taking water cooling as an example, the cooling control parameters include water temperature control, flow rate control, and time control. The corresponding cooling effect is the cooling rate and cooling amplitude of the product at a specific injection temperature. Based on the acquired cooling control parameters, cooling performance parameters and cooling rate parameters are analyzed to determine cooling performance characteristics and cooling rate characteristics. Cooling performance characteristics are used to determine the strength of mold cooling (i.e., the cooling amplitude), while cooling rate characteristics are used to determine the speed of mold cooling (i.e., the cooling rate). Furthermore, the cooling performance characteristics and cooling rate characteristics are correlated and mapped to construct correlation mapping factors. The cooling control database is then constructed based on these correlation mapping factors.

[0038] like Figure 3As shown, the method provided in this application embodiment further includes:

[0039] Determine whether the injection temperature data is within the preset cooling range;

[0040] If not, a pause command is generated, and cooling is paused according to the pause command, while checking the adjacent critical values ​​of the injected temperature data;

[0041] Based on the adjacent critical values, the target injection mold is either placed on hold or heated until the injection temperature data is within the preset cooling range.

[0042] If so, the cooling control database is traversed based on the injected temperature data to obtain N cooling schemes.

[0043] The system determines whether the injection temperature data falls within a preset cooling range. This preset cooling range is a pre-defined interval where the injection temperature needs to be cooled; the specific value is set by professionals based on the actual conditions of different materials. If it does not fall within this range, a pause command is generated, and cooling is paused according to the command. Simultaneously, the system checks adjacent critical values ​​of the injection temperature data to determine whether the temperature is too high to warrant cooling or too low to require cooling. Based on these adjacent critical values, the target injection mold is either paused or heated until the injection temperature data falls within the preset cooling range. If it does fall within this range, the system iterates through the cooling control database to obtain N cooling schemes.

[0044] Based on the N cooling schemes and the target injection mold, a fitness analysis is performed. The optimization of the cooling control process is then carried out according to the fitness results, and the cooling control process result is determined.

[0045] The target plastic injection mold is cooled based on the cooling control processing results.

[0046] After acquiring N cooling schemes corresponding to the injection temperature data, a fitness analysis is performed on these N cooling schemes and the target injection mold. Based on the fitness results, the cooling control process is optimized to determine the final cooling control result. Finally, the target plastic injection mold is cooled based on the cooling control result. This achieves intelligent acquisition of the cooling control method for the injection mold, improving the accuracy of cooling control and enhancing the stability of injection molded product quality.

[0047] The method provided in this application embodiment also includes:

[0048] Based on the first cooling scheme, extract the i-th set of cooling parameter control data;

[0049] Perform fitness analysis on the i-th group of cooling parameter control data to obtain the fitness of the k-th group of control parameters;

[0050] Determine whether the fitness of the i-th group of cooling parameters is greater than or equal to the fitness of the (i-1)-th group of cooling parameters;

[0051] If the data is greater than or equal to the i-1th group of cooling parameter control data, add the i-1th group of cooling parameter control data to the elimination data group; if the data is less than the i-th group of cooling parameter control data, add the i-th group of cooling parameter control data to the elimination data group.

[0052] Determine if i satisfies the tabu list update cycle;

[0053] If satisfied, input the fitness of the i-th group of cooling parameters or the fitness of the (i-1)-th group of cooling parameters into the taboo table for updating, and determine whether the taboo table update count meets the preset update count.

[0054] If satisfied, obtain the taboo table update value and set it as the cooling control processing result.

[0055] After obtaining N cooling schemes corresponding to the injection temperature data, based on the first cooling scheme (where the first cooling scheme is one of the obtained N cooling schemes), the i-th group of cooling parameter control data is extracted, and the i-th group of cooling parameter control data is the control data corresponding to the first cooling scheme. Subsequently, fitness analysis is performed on the i-th group of cooling parameter control data to obtain the k-th group of control parameter fitness, which is the fitness data of the i-th group of cooling parameter control data. It is then determined whether the fitness of the i-th group of cooling parameters is greater than or equal to the fitness of the (i-1)-th group of cooling parameters, where the (i-1)-th group of cooling parameter fitness is the fitness analysis result of the parameter control data obtained before performing fitness analysis on the i-th group of cooling parameter control data. If it is greater than or equal to, the (i-1)-th group of cooling parameter control data is added to the elimination data group. If it is less than, the i-th group of cooling parameter control data is added to the elimination data group. Subsequently, it is determined whether i meets the taboo table update cycle, where the taboo table update cycle is the taboo table update time cycle set by the technician. If satisfied, input the fitness of the i-th group of cooling parameters or the (i-1)-th group of cooling parameters into the taboo table for updating, and determine whether the taboo table update count meets the preset update count. If satisfied, obtain the taboo table update value and set it as the cooling control processing result.

[0056] The method provided in this application embodiment also includes:

[0057] Based on the i-th group of cooling parameter control data, obtain the i-th group of cooling degree parameter characteristics and the i-th group of cooling rate parameter characteristics;

[0058] A first weight is assigned to the i-th group of cooling degree parameter features, and a second weight is assigned to the i-th group of cooling rate parameter features;

[0059] The fitness of the i-th group of cooling parameters is obtained based on the first weight and the i-th group of cooling degree parameter characteristics, as well as the second weight and the i-th group of cooling rate parameter characteristics.

[0060] When obtaining the fitness of cooling parameters, based on the i-th group of cooling parameter control data, the i-th group of cooling degree parameter features and the i-th group of cooling rate parameter features are obtained, where the i-th group of cooling degree parameter features and the i-th group of cooling rate parameter features are the corresponding parameter features of historical applications of the i-th group of cooling parameter control data. Specifically, the i-th group of cooling rate parameter features is the temperature reduction per unit time of the normalized i-th group of cooling parameter control data, and the i-th group of cooling parameter features is the total temperature reduction data of the normalized i-th group of cooling parameter control data. Subsequently, a first weight is assigned to the i-th group of cooling parameter features, and a second weight is assigned to the i-th group of cooling rate parameter features. The specific weight data is set based on the actual cooling preference. Based on the first weight and the i-th group of cooling parameter features, and the second weight and the i-th group of cooling rate parameter features, the fitness of the i-th group of cooling parameters is calculated.

[0061] The method provided in this application embodiment also includes:

[0062] Based on the taboo table, extract the initial value of the taboo table, wherein the initial value of the taboo table has taboo cooling parameter fitness;

[0063] Determine whether the fitness of the i-th group of cooling parameters or the (i-1)-th group of cooling parameters is greater than or equal to the fitness of the forbidden cooling parameters;

[0064] If it is greater than or equal to, the initial value of the taboo table is replaced according to the i-th group of cooling parameter control data or the (i-1)-th group of cooling parameter record data, and set as the taboo table update value;

[0065] If it is less than, set the initial value of the tabu table to the updated value of the tabu table.

[0066] Based on the taboo table, an initial value is extracted. This initial value has taboo cooling parameter fitness and represents taboo data before updates, including the initially set optimal control parameters. After subsequent updates, it represents the updated optimal control parameters. It is determined whether the fitness of the i-th group of cooling parameters or the (i-1)-th group of cooling parameters is greater than or equal to the taboo cooling parameter fitness. If it is greater than or equal to, i.e., when the fitness of the i-th group of cooling parameters or the (i-1)-th group of cooling parameters is greater than or equal to the taboo cooling parameter fitness, then the fitness of the i-th group of control parameters or the (i-1)-th group of control parameters is considered superior to the taboo control parameter fitness in the current taboo table. Therefore, the initial value of the taboo table is replaced by the larger parameter record from the i-th group of control parameter records or the (i-1)-th group of control parameter records, and set as the updated taboo table value. If it is less than, the initial value of the taboo table is set as the updated taboo table value.

[0067] The method provided in this application embodiment also includes:

[0068] Configure the mold cooling verification cycle;

[0069] During the mold cooling verification cycle, the temperature of the target plastic injection mold is collected, and the mold cooling parameters based on the temperature collection results are verified.

[0070] The verification results of mold cooling parameters are used as early warning features to monitor and identify abnormal cooling temperatures of the target plastic injection mold.

[0071] A mold cooling verification cycle is configured, which is a cooling performance verification cycle. Upon reaching the specified mold cooling verification cycle, the temperature of the target plastic injection mold is collected, and the mold cooling parameters based on the collected temperature are verified to obtain the mold's cooling data. The mold cooling parameter verification results are used as early warning features to monitor and identify abnormal cooling temperatures of the target plastic injection mold. The mold cooling parameter verification results are compared with control parameters, and the comparison results are obtained. When the comparison result is significantly greater than or significantly less than the control parameters, an abnormality in the mold cooling parameter verification results is detected, and a cooling temperature abnormality warning is issued.

[0072] The technical solution provided by this invention acquires the structure of a target plastic injection mold through three-dimensional image acquisition using an industrial CCD. Plastic material is injected based on the target injection mold structure to determine injection temperature data. This injection temperature data is used as index data to traverse a cooling control database, obtaining N cooling schemes, where N is a positive integer greater than 1. A fitness analysis is performed between these N cooling schemes and the target injection mold. Based on the fitness results, optimization of the cooling control process is performed to determine the cooling control result. Cooling control is then applied to the target plastic injection mold based on this result. This achieves intelligent acquisition of the cooling control method for the injection mold, improving the accuracy of cooling control and enhancing the quality stability of the injection molded product. It solves the technical problem in existing technologies where low cooling control accuracy in injection mold cooling control leads to poor quality stability of injection molded products.

[0073] Example 2

[0074] Based on the same inventive concept as the cooling control method for a plastic injection mold in the foregoing embodiments, this invention also provides a system for cooling control of a plastic injection mold. The system can be implemented in hardware and / or software, and is generally integrated into an electronic device to execute the method provided in any embodiment of this invention. For example... Figure 4 As shown, the system includes:

[0075] The structure acquisition module 11 is used to acquire the structure of the target plastic injection mold, which is obtained by three-dimensional image acquisition using an industrial CCD.

[0076] Temperature data acquisition module 12 is used to inject plastic material according to the target injection mold structure and determine injection temperature data;

[0077] The cooling scheme acquisition module 13 is used to use the injected temperature data as index data to traverse the cooling control database and obtain N cooling schemes, where N is a positive integer greater than 1.

[0078] The control optimization module 14 is used to perform a fitness analysis based on the N cooling schemes and the target injection mold, optimize the cooling control process according to the fitness results, and determine the cooling control process result.

[0079] The cooling control module 15 is used to control the cooling of the target plastic injection mold based on the cooling control processing results.

[0080] Furthermore, the cooling scheme acquisition module 13 is also used for:

[0081] Cooling control parameters of the target plastic injection mold are collected based on big data.

[0082] Based on the cooling control parameters, analyze the cooling performance parameters and cooling rate parameters to determine the cooling performance characteristics and cooling rate characteristics;

[0083] The cooling performance characteristics and the cooling rate characteristics are correlated and mapped to construct a correlation mapping factor;

[0084] A cooling control database is constructed based on the aforementioned correlation mapping factors.

[0085] Furthermore, the cooling scheme acquisition module 13 is also used for:

[0086] Determine whether the injection temperature data is within the preset cooling range;

[0087] If not, a pause command is generated, and cooling is paused according to the pause command, while checking the adjacent critical values ​​of the injected temperature data;

[0088] Based on the adjacent critical values, the target injection mold is either placed on hold or heated until the injection temperature data is within the preset cooling range.

[0089] If so, the cooling control database is traversed based on the injected temperature data to obtain N cooling schemes.

[0090] Furthermore, the control optimization module 14 is also used for:

[0091] Based on the first cooling scheme, extract the i-th set of cooling parameter control data;

[0092] Perform fitness analysis on the i-th group of cooling parameter control data to obtain the fitness of the k-th group of control parameters;

[0093] Determine whether the fitness of the i-th group of cooling parameters is greater than or equal to the fitness of the (i-1)-th group of cooling parameters;

[0094] If the data is greater than or equal to the i-1th group of cooling parameter control data, add the i-1th group of cooling parameter control data to the elimination data group; if the data is less than the i-th group of cooling parameter control data, add the i-th group of cooling parameter control data to the elimination data group.

[0095] Determine if i satisfies the tabu list update cycle;

[0096] If satisfied, input the fitness of the i-th group of cooling parameters or the fitness of the (i-1)-th group of cooling parameters into the taboo table for updating, and determine whether the taboo table update count meets the preset update count.

[0097] If satisfied, obtain the taboo table update value and set it as the cooling control processing result.

[0098] Furthermore, the control optimization module 14 is also used for:

[0099] Based on the i-th group of cooling parameter control data, obtain the i-th group of cooling degree parameter characteristics and the i-th group of cooling rate parameter characteristics;

[0100] A first weight is assigned to the i-th group of cooling degree parameter features, and a second weight is assigned to the i-th group of cooling rate parameter features;

[0101] The fitness of the i-th group of cooling parameters is obtained based on the first weight and the i-th group of cooling degree parameter characteristics, as well as the second weight and the i-th group of cooling rate parameter characteristics.

[0102] Furthermore, the control optimization module 14 is also used for:

[0103] Based on the taboo table, extract the initial value of the taboo table, wherein the initial value of the taboo table has taboo cooling parameter fitness;

[0104] Determine whether the fitness of the i-th group of cooling parameters or the (i-1)-th group of cooling parameters is greater than or equal to the fitness of the forbidden cooling parameters;

[0105] If it is greater than or equal to, the initial value of the taboo table is replaced according to the i-th group of cooling parameter control data or the (i-1)-th group of cooling parameter record data, and set as the taboo table update value;

[0106] If it is less than, set the initial value of the tabu table to the updated value of the tabu table.

[0107] Furthermore, the control optimization module 14 is also used for:

[0108] Configure the mold cooling verification cycle;

[0109] During the mold cooling verification cycle, the temperature of the target plastic injection mold is collected, and the mold cooling parameters based on the temperature collection results are verified.

[0110] The verification results of mold cooling parameters are used as early warning features to monitor and identify abnormal cooling temperatures of the target plastic injection mold.

[0111] The various units and modules included are divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0112] Example 3

[0113] Figure 5This is a schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present invention, showing a block diagram of an exemplary electronic device suitable for implementing the embodiments of the present invention. Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality or scope of the embodiments of the present invention. Figure 5 As shown, the electronic device includes a processor 31, a memory 32, an input device 33, and an output device 34; the number of processors 31 in the electronic device can be one or more. Figure 5 Taking a processor 31 as an example, the processor 31, memory 32, input device 33, and output device 34 in an electronic device can be connected via a bus or other means. Figure 5 Taking the example of a connection between China and Israel via a bus.

[0114] The memory 32, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the cooling control method for a plastic injection mold in this embodiment of the invention. The processor 31 executes various functional applications and data processing of the computer device by running the software programs, instructions, and modules stored in the memory 32, thereby realizing the aforementioned cooling control method for a plastic injection mold.

[0115] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A cooling control method of a plastic injection mold characterized by, The method comprises: acquiring a target plastic injection mold structure, the target plastic injection mold structure being obtained by three-dimensional image acquisition through an industrial CCD; determining injection temperature data according to the target plastic injection mold structure; taking the injection temperature data as index data, traversing a cooling control database to obtain N cooling schemes, wherein N is a positive integer greater than 1; performing fitness analysis on the N cooling schemes and the target injection mold, and performing optimization on the cooling control processing according to the fitness result to determine a cooling control processing result; based on the cooling control processing result, performing cooling control on the target plastic injection mold.

2. The method of claim 1, wherein, The method further comprises: collecting cooling control parameters of the target plastic injection mold based on big data; determining cooling performance characteristics and cooling rate characteristics according to the cooling performance parameters and the cooling rate parameters; correlating and mapping the cooling performance characteristics and the cooling rate characteristics to construct a correlation mapping factor; constructing a cooling control database according to the correlation mapping factor.

3. The method of claim 1, wherein, The method further comprises: determining whether the injection temperature data is in a preset cooling interval; if not, generating a pause instruction, pausing cooling according to the pause instruction, and checking adjacent critical values of the injection temperature data; performing standby or warming operation on the target injection mold according to the adjacent critical values until the injection temperature data is in the preset cooling interval; if so, traversing the cooling control database according to the injection temperature data to obtain N cooling schemes.

4. The method of claim 1, wherein, The method further comprises: extracting the i-th set of cooling parameter control data according to the first cooling scheme; performing fitness analysis on the i-th set of cooling parameter control data to obtain the k-th set of control parameter fitness; determining whether the i-th set of cooling parameter fitness is greater than or equal to the i-1-th set of cooling parameter fitness; if greater than or equal to, adding the i-1-th set of cooling parameter control data to the elimination data set, and if less than, adding the i-th set of cooling parameter control data to the elimination data set; determining whether i satisfies the tabu list update period; if so, inputting the i-th set of cooling parameter fitness or the i-1-th set of cooling parameter fitness into the tabu list for updating, and determining whether the number of tabu list updates satisfies a preset update number; if so, obtaining a tabu list update value as the cooling control processing result.

5. The method of claim 4, wherein, The method further comprises: obtaining the i-th set of cooling degree parameter characteristics and the i-th set of cooling speed parameter characteristics according to the i-th set of cooling parameter control data; setting a first weight for the i-th set of cooling degree parameter characteristics and a second weight for the i-th set of cooling speed parameter characteristics; calculating the i-th set of cooling parameter fitness according to the first weight and the i-th set of cooling degree parameter characteristics, and the second weight and the i-th set of cooling speed parameter characteristics.

6. The method of claim 4, wherein, The method further comprises: extracting a tabu list initial value from the tabu list, wherein the tabu list initial value has a tabu cooling parameter fitness; determining whether the i-th set of cooling parameter fitness or the i-1-th set of cooling parameter fitness is greater than or equal to the taboo cooling parameter fitness; if greater than or equal to, replacing the initial value of the taboo table with the i-th set of cooling parameter control data or the i-1-th set of cooling parameter record data, and setting the taboo table update value; if less than, setting the initial value of the taboo table as the taboo table update value.

7. The method of claim 1, wherein, The method further comprises: configuring a mold cooling verification period; collecting the temperature of the target plastic injection mold during the mold cooling verification period, and performing mold cooling parameter verification on the temperature collection result; using the mold cooling parameter verification result as a pre-warning feature to monitor and identify the cooling temperature anomaly of the target plastic injection mold.

8. A cooling control system for a plastic injection mold, characterized by, The system comprises: a structure acquisition module configured to acquire a target plastic injection mold structure, the target plastic injection mold structure being obtained by three-dimensional image acquisition through an industrial CCD; a temperature data acquisition module configured to determine injection temperature data according to the target plastic injection mold structure and the injection of plastic material; a cooling scheme acquisition module configured to use the injection temperature data as index data to traverse a cooling control database and obtain N cooling schemes, where N is a positive integer greater than 1; a control optimization module configured to perform fitness analysis on the N cooling schemes and a target injection mold, perform optimization of cooling control processing according to the fitness result, and determine a cooling control processing result; a cooling control module configured to perform cooling control on the target plastic injection mold based on the cooling control processing result.

9. An electronic device, comprising: The electronic device comprises: a memory configured to store executable instructions; a processor configured to execute the executable instructions stored in the memory to implement the cooling control method of the plastic injection mold according to any one of claims 1 to 7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the cooling control method of the plastic injection mold according to any one of claims 1 to 7.

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