Injection mold and injection molding method

Abstract

The invention relates to an injection mold and an injection molding method, and belongs to the technical field of injection molding.Cooling performance data of cooling liquid of a cooling system within preset time are predicted according to a cooling performance prediction model of the cooling liquid, so that injection molding temperature information in the injection molding process is collected through a temperature sensor; the method comprises the following steps: acquiring a temperature evaluation result by identifying and analyzing injection molding temperature information in an injection molding process, finally generating a control strategy according to the temperature evaluation result and cooling performance data of a cooling liquid of a cooling system within a preset time, and performing injection molding control on an injection mold in the injection molding process according to the control strategy. By evaluating the performance of the cooling liquid in the cooling system and analyzing the real-time injection molding temperature, the injection molding process is evaluated and analyzed, then the cooling process is intelligently controlled, accurate control is achieved, the injection molding success rate of injection molded parts is increased, the defective rate is reduced, and therefore the injection molding cost is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of injection molding, and in particular to an injection mold and an injection molding method. Background Art

[0002] Injection mold is a tool for producing plastic products; it is also a tool that gives plastic products a complete structure and precise size. Injection mold is also a processing method used in mass production of parts, mainly used in the industrial field. The injection mold process is to inject the heated and melted material into the mold cavity by high pressure, and obtain the molded product after cooling and solidification; it is divided into thermosetting plastic mold and thermoplastic plastic mold according to the molding characteristics. There are many molding methods for injection molded products, such as blow molding, injection molding, extrusion molding, etc. Related mold technology has become one of the important indicators to measure a country's industrial and manufacturing level. Among them, the method of producing plastic products through injection molds is relatively effective, and injection molding is widely used. The injection molding process can be divided into the following stages: mold closing, injection, pressure holding, mold opening, and product removal. In the process of injection molding, the cooling process is relatively important for the product molding process and product quality. With the increasingly urgent demand for the precision development of injection molds, it is necessary to improve the precision and production efficiency of the plastic product production process. Cooling the injection mold is a critical step. During the cooling process, the temperature of the mold surface needs to be collected because it has a great influence on the fluidity, curing speed and molding quality of the plastic raw materials. However, nowadays, the cooling performance degradation of the cooling system is not considered during the cooling process of injection molding, which may lead to cooling anomalies during the cooling process, which will lead to an increase in the defective rate during the injection molding process. Summary of the invention

[0003] The invention overcomes the deficiencies of the prior art and provides an injection mold and an injection molding method.

[0004] To achieve the above object, the technical solution adopted by the present invention is: A first aspect of the present invention provides an injection mold, specifically comprising: Injection mold body, A cooling system connected to the injection mold body, through which a coolant is provided and the injection temperature during the injection molding process is controlled by the coolant; Temperature sensor, responsible for obtaining injection temperature information during the injection molding process; The control system is responsible for controlling the flow data of the coolant in the cooling system within a unit time according to the injection temperature information during the injection molding process.

[0005] A second aspect of the present invention provides an injection molding method, wherein the injection mold specifically comprises the following steps: Acquiring coolant performance degradation characteristic data of the cooling system at each operating frequency, and constructing a cooling performance prediction model of the coolant according to the coolant performance degradation characteristic data of the cooling system at each operating frequency; Predicting the cooling performance data of the coolant in the cooling system within a preset time according to the cooling performance prediction model of the coolant; The injection molding temperature information during the injection molding process is collected through the temperature sensor, and the temperature evaluation result is obtained by identifying and analyzing the injection molding temperature information during the injection molding process; A control strategy is generated according to the temperature evaluation result and the cooling performance data of the coolant of the cooling system within a preset time, and the injection mold is injection-controlled during the injection molding process according to the control strategy.

[0006] Furthermore, in the injection molding method, coolant performance degradation characteristic data of the cooling system at each operating frequency is obtained, and a cooling performance prediction model of the coolant is constructed according to the coolant performance degradation characteristic data of the cooling system at each operating frequency, specifically including: Acquire coolant performance degradation characteristic data of the cooling system at each operating frequency, and construct a cooling performance prediction model of the coolant based on a deep neural network, with the operating frequency as the first node and the coolant performance degradation characteristic data as the second node; Constructing a directed description relationship, connecting the first node and the second node based on the directed description relationship, constructing a topological structure graph, obtaining a related adjacency matrix based on the topological structure graph, and obtaining an adjacency matrix for each timestamp; Taking the adjacency matrix of each timestamp as a state vector, calculating the transition probability value of the state vector to the next state vector, and if the transition probability value is greater than a preset probability value, updating the current state vector to the next state vector; If the transfer probability value is not greater than the preset probability value, the current state vector is maintained unchanged, the processed state vector is obtained, and a state vector matrix based on a time series is constructed. The state vector matrix based on a time series is input into the cooling performance prediction model of the coolant for training.

[0007] Furthermore, in the injection molding method, the state vector matrix based on the time series is input into the cooling performance prediction model of the coolant for training, specifically: Setting a prediction accuracy threshold, inputting the time series-based state vector matrix into the cooling performance prediction model of the coolant for training, and obtaining the prediction accuracy of the cooling performance prediction model of the coolant; Determine whether the prediction accuracy of the cooling performance prediction model of the coolant is greater than the prediction accuracy threshold, and if so, the training of the cooling performance prediction model of the coolant is terminated; When the prediction accuracy of the cooling performance prediction model of the coolant is not greater than the prediction accuracy threshold, the cooling performance prediction model of the coolant is continuously trained until it is greater than the prediction accuracy threshold.

[0008] Furthermore, in the injection molding method, the cooling performance data of the coolant in the cooling system within a preset time is predicted according to the cooling performance prediction model of the coolant, specifically: Obtaining coolant performance change characteristic data within a preset time and operating frequency data within a preset time; Inputting the coolant performance change characteristic data within the preset time and the operating frequency data within the preset time into the coolant cooling performance prediction model for prediction; By prediction, the cooling performance data of the coolant in the cooling system within a preset time is obtained, and the cooling performance data of the coolant in the cooling system within the preset time is output.

[0009] Furthermore, in the injection molding method, the injection molding temperature information during the injection molding process is collected by a temperature sensor, and the injection molding temperature information during the injection molding process is identified and analyzed to obtain a temperature evaluation result, specifically: Setting an injection temperature threshold, and collecting injection temperature information during the injection molding process through a temperature sensor, and determining whether the injection temperature information during the injection molding process is greater than the injection temperature threshold; When the injection temperature information during the injection molding process is greater than the injection temperature threshold, the injection temperature information during the injection molding process is used as abnormal temperature information, and the abnormal temperature information is output as a temperature evaluation result.

[0010] When the injection temperature information during the injection molding process is not greater than the injection temperature threshold, the injection temperature information during the injection molding process is used as normal temperature information, and the normal temperature information is output as a temperature evaluation result.

[0011] Furthermore, in the injection molding method, a control strategy is generated according to the temperature evaluation result and the cooling performance data of the coolant of the cooling system within a preset time, and the injection molding of the injection mold is controlled during the injection molding process according to the control strategy, specifically: Acquire cooling requirement information during the injection molding process, and when the temperature evaluation result is abnormal temperature information, determine whether the cooling performance data of the coolant of the cooling system within a preset time is greater than the cooling requirement information during the injection molding process; If it is greater than, then the flow data of the coolant in the cooling system within a unit time is uniformly increased again, and the cooling system is controlled according to the flow data of the coolant in the cooling system within a unit time; By controlling, the injection molding temperature information in the injection molding process within a preset time is continuously collected, and it is determined whether the injection molding temperature information in the injection molding process within the preset time is abnormal temperature information; When the injection temperature information during the injection molding process within the preset time is abnormal temperature information, the flow data of the coolant in the cooling system within the unit time is readjusted until it is no longer abnormal temperature information; When the injection temperature information during the injection molding process within the preset time is not abnormal temperature information, the cooling system is continuously controlled according to the flow data of the coolant within the unit time of the cooling system.

[0012] A third aspect of the present invention provides an electronic device, the electronic device comprising a memory and a processor, the memory comprising an injection molding method program, and when the injection molding method program is executed by the processor, the following steps are implemented: Acquiring coolant performance degradation characteristic data of the cooling system at each operating frequency, and constructing a cooling performance prediction model of the coolant according to the coolant performance degradation characteristic data of the cooling system at each operating frequency; Predicting the cooling performance data of the coolant in the cooling system within a preset time according to the cooling performance prediction model of the coolant; The injection molding temperature information during the injection molding process is collected through the temperature sensor, and the temperature evaluation result is obtained by identifying and analyzing the injection molding temperature information during the injection molding process; A control strategy is generated according to the temperature evaluation result, and injection control is performed on the injection mold during the injection molding process according to the control strategy. The present invention solves the defects existing in the background technology and has the following beneficial effects: The present invention obtains the coolant performance degradation characteristic data of the cooling system under each operating frequency, and constructs a cooling performance prediction model of the coolant according to the coolant performance degradation characteristic data of the cooling system under each operating frequency, and then predicts the cooling performance data of the coolant of the cooling system within a preset time according to the cooling performance prediction model of the coolant, thereby collecting the injection temperature information during the injection molding process through a temperature sensor, and obtaining the temperature evaluation result by identifying and analyzing the injection temperature information during the injection molding process, and finally generating a control strategy according to the temperature evaluation result and the cooling performance data of the coolant of the cooling system within the preset time, and performing injection molding control on the injection mold during the injection molding process according to the control strategy. The present invention evaluates and analyzes the injection molding process by evaluating the performance of the coolant in the cooling system and combining the analysis of the real-time injection molding temperature, and then intelligently controls the cooling process, realizes precise control, improves the injection molding success rate of the injection molded parts, reduces the defective rate, and thus reduces the injection molding cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying creative work.

[0014] Figure 1 The overall structural diagram of the injection mold is shown; Figure 2 An overall method flow chart of the injection molding method is shown; Figure 3 A device schematic diagram of an electronic device is shown. DETAILED DESCRIPTION

[0015] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0016] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0017] like Figure 1 As shown, the first aspect of the present invention provides an injection mold, specifically comprising: Injection mold body 1, A cooling system 2 connected to the injection mold body 1, through which a coolant is provided, and through which the injection temperature during the injection molding process is controlled; Temperature sensor, responsible for obtaining injection temperature information during the injection molding process; The control system 3 is responsible for controlling the flow data of the coolant in the cooling system within a unit time according to the injection temperature information during the injection molding process.

[0018] It should be noted that if Figure 1 As shown, the injection mold body 1 is connected to the cooling system 1 through a pipeline.

[0019] like Figure 2 As shown, the second aspect of the present invention provides an injection molding method, an injection mold, and specifically comprises the following steps: S102: acquiring coolant performance degradation characteristic data of the cooling system at each operating frequency, and constructing a cooling performance prediction model of the coolant according to the coolant performance degradation characteristic data of the cooling system at each operating frequency; S104: predicting cooling performance data of the coolant in the cooling system within a preset time according to the cooling performance prediction model of the coolant; S106: collecting injection temperature information during the injection molding process through a temperature sensor, and obtaining a temperature evaluation result by identifying and analyzing the injection temperature information during the injection molding process; S108: Generate a control strategy based on the temperature evaluation result and the cooling performance data of the coolant of the cooling system within a preset time, and perform injection control on the injection mold during the injection molding process according to the control strategy.

[0020] It should be noted that the present invention evaluates and analyzes the injection molding process by evaluating the performance of the coolant in the cooling system and analyzing the real-time injection molding temperature, and then intelligently controls the cooling process to achieve precise control, improve the injection molding success rate of injection molded parts, reduce the defective rate, and thus reduce the injection molding cost.

[0021] Furthermore, in the injection molding method, coolant performance degradation characteristic data of the cooling system at each operating frequency is obtained, and a cooling performance prediction model of the coolant is constructed according to the coolant performance degradation characteristic data of the cooling system at each operating frequency, specifically including: Acquire coolant performance degradation characteristic data of the cooling system at each operating frequency, and construct a cooling performance prediction model of the coolant based on a deep neural network, with the operating frequency as the first node and the coolant performance degradation characteristic data as the second node; Constructing a directed description relationship, connecting the first node and the second node based on the directed description relationship, constructing a topological structure graph, obtaining a related adjacency matrix based on the topological structure graph, and obtaining an adjacency matrix for each timestamp; The adjacency matrix of each timestamp is used as a state vector, and the transition probability value of the state vector to the next state vector is calculated. If the transition probability value is greater than the preset probability value, the current state vector is updated to the next state vector; If the transfer probability value is not greater than the preset probability value, the current state vector is maintained unchanged, the processed state vector is obtained, and a state vector matrix based on a time series is constructed. The state vector matrix based on a time series is input into the cooling performance prediction model of the coolant for training.

[0022] It should be noted that, since the cooling system will degrade after a certain number of years of use, the coolant performance degradation characteristic data include the temperature drop within a unit time, the temperature increase of the coolant within a unit time, the heat removed by the coolant within a unit time, etc. Among them, the state transfer is actually equivalent to a Markov model, and the transfer probability value of the state vector to the next state vector is calculated through the Markov chain. If the transfer probability value is greater than the preset probability value, the current state vector is updated to the next state vector. If the transfer probability value is not greater than the preset probability value, the current state vector is maintained unchanged, and the processed state vector is obtained to realize the update of the state, thereby improving the prediction accuracy of the coolant cooling performance prediction model.

[0023] Furthermore, in the injection molding method, the state vector matrix based on the time series is input into the cooling performance prediction model of the coolant for training, specifically: A prediction accuracy threshold is set, and a state vector matrix based on the time series is input into the cooling performance prediction model of the coolant for training, so as to obtain the prediction accuracy of the cooling performance prediction model of the coolant; Determine whether the prediction accuracy of the cooling performance prediction model of the coolant is greater than a prediction accuracy threshold, and if so, the training of the cooling performance prediction model of the coolant is terminated; When the prediction accuracy of the cooling performance prediction model of the coolant is not greater than the prediction accuracy threshold, the cooling performance prediction model of the coolant is continuously trained until it is greater than the prediction accuracy threshold.

[0024] Furthermore, in the injection molding method, the cooling performance data of the coolant in the cooling system within a preset time is predicted according to the cooling performance prediction model of the coolant, specifically: Obtaining coolant performance change characteristic data within a preset time and operating frequency data within a preset time; Inputting the coolant performance change characteristic data within a preset time and the working frequency data within a preset time into the coolant cooling performance prediction model for prediction; Through prediction, the cooling performance data of the coolant in the cooling system within a preset time is obtained, and the cooling performance data of the coolant in the cooling system within the preset time is output.

[0025] Furthermore, in the injection molding method, the injection molding temperature information during the injection molding process is collected by a temperature sensor, and the injection molding temperature information during the injection molding process is identified and analyzed to obtain a temperature evaluation result, specifically: Set an injection temperature threshold, and collect injection temperature information during the injection molding process through a temperature sensor to determine whether the injection temperature information during the injection molding process is greater than the injection temperature threshold; When the injection temperature information during the injection molding process is greater than the injection temperature threshold, the injection temperature information during the injection molding process is regarded as abnormal temperature information, and the abnormal temperature information is output as the temperature evaluation result.

[0026] When the injection temperature information during the injection molding process is not greater than the injection temperature threshold, the injection temperature information during the injection molding process is regarded as normal temperature information, and the normal temperature information is output as the temperature evaluation result.

[0027] It should be noted that this method can be used to evaluate whether the temperature is abnormal, thereby performing intelligent temperature control.

[0028] Furthermore, in the injection molding method, a control strategy is generated according to the temperature evaluation result and the cooling performance data of the coolant of the cooling system within a preset time, and the injection molding of the injection mold is controlled during the injection molding process according to the control strategy, specifically: Acquire cooling demand information during the injection molding process. When the temperature evaluation result is abnormal temperature information, determine whether the cooling performance data of the coolant of the cooling system within a preset time is greater than the cooling demand information during the injection molding process; If it is greater than, the flow data of the coolant in the cooling system within a unit time is evenly increased again, and the cooling system is controlled according to the flow data of the coolant in the cooling system within a unit time; By controlling, the injection molding temperature information in the injection molding process within the preset time is continuously collected, and it is determined whether the injection molding temperature information in the injection molding process within the preset time is abnormal temperature information; When the injection temperature information during the injection molding process within the preset time is abnormal temperature information, the flow data of the coolant in the cooling system within the unit time is readjusted until it is no longer abnormal temperature information; When the injection temperature information during the injection molding process within the preset time is not abnormal temperature information, the cooling system is continuously controlled according to the flow data of the coolant within the unit time of the cooling system.

[0029] It should be noted that the injection molding temperature during the injection molding process can be accurately controlled through this method. The cooling requirement information during the injection molding process is variable and depends on the difference between the real-time injection molding temperature and the injection molding temperature threshold.

[0030] In addition, the method further comprises: If the cooling performance data of the coolant of the cooling system within the preset time is not greater than the cooling demand information during the injection molding process, the cooling performance data of the coolant of each cooling system in the current target area within the preset time is obtained; Introducing a genetic algorithm, and setting a genetic algebra according to the genetic algorithm, to obtain the number of injection molding devices corresponding to the cooling performance data of the coolant of the cooling system within a preset time that is not greater than the cooling demand information during the injection molding process; Initialize the working injection molding device set according to the number of injection molding devices corresponding to the cooling performance data of the coolant of the cooling system within a preset time that is not greater than the cooling demand information during the injection molding process; Acquire cooling performance data of the coolant of each injection molding device in the set of injection molding devices that are initialized according to the cooling performance data of the coolant of each cooling system in the current target area within a preset time; Determining whether the cooling performance data of the coolant of each injection molding device in the set of injection molding devices for the initialization operation is greater than the cooling requirement information during the injection molding process; If the cooling performance data of the coolant of each injection molding device in the set of injection molding devices initialized to work is not all greater than the cooling requirement information during the injection molding process, then adjusting the set of injection molding devices working based on the genetic algebra, updating the working injection molding devices in the set of working injection molding devices until the cooling performance data of the coolant of each injection molding device is greater than the cooling requirement information during the injection molding process; If the cooling performance data of the coolant of each injection molding device in the initialized working injection molding device set is greater than the cooling requirement information during the injection molding process, the working injection molding device set is output, and injection molding allocation is performed according to the working injection molding device set.

[0031] It should be noted that this method can reallocate the work of injection molded parts whose cooling performance data of the coolant in the cooling system within a preset time is not greater than the cooling demand information during the injection molding process, thereby reducing the generation of abnormal injection molded parts.

[0032] In addition, the method further comprises: If the maximum genetic generation is reached, if the cooling performance data of the coolant of each injection molding device in the set of injection molding devices for the initialization work is not all greater than the cooling requirement information during the injection molding process, obtain the maximum frequency of the cooling performance data of the coolant of the injection molding device in the set of injection molding devices for the initialization work being greater than the cooling requirement information during the injection molding process; The set of injection molding devices for which the cooling performance data of the coolant of the injection molding device is greater than the maximum frequency of the cooling demand information during the injection molding process is initialized is taken as the optimal solution; The cooling performance data of the coolant is obtained to be no greater than the injection molding device corresponding to the cooling demand information during the injection molding process; An injection stop instruction is set, and according to the injection stop instruction, injection stop control is performed on the injection device corresponding to the cooling performance data of the coolant being no greater than the cooling requirement information during the injection process.

[0033] It should be noted that, if the maximum genetic generation is reached, if the cooling performance data of the coolant of each injection molding device in the set of injection molding devices for the initialization work is not all greater than the cooling requirement information during the injection molding process, then the injection molding devices in the set of injection molding devices for the initialization work whose cooling performance data of the coolant is greater than the cooling requirement information during the injection molding process are found, and the injection molding devices in the set of injection molding devices for the initialization work whose cooling performance data of the coolant is greater than the cooling requirement information during the injection molding process are taken as the optimal solution, so as to stop injection molding control for the injection molding devices corresponding to the cooling performance data of the coolant not greater than the cooling requirement information during the injection molding process according to the injection stop instruction, thereby improving the rationality of control.

[0034] A third aspect of the present invention provides an electronic device 4, the electronic device 4 includes a memory 41 and a processor 42, the memory 41 includes an injection molding method program, and when the injection molding method program is executed by the processor 42, the following steps are implemented: Acquire coolant performance degradation characteristic data of the cooling system at each operating frequency, and construct a cooling performance prediction model of the coolant according to the coolant performance degradation characteristic data of the cooling system at each operating frequency; Predicting the cooling performance data of the coolant in the cooling system within a preset time according to the cooling performance prediction model of the coolant; The injection molding temperature information during the injection molding process is collected through the temperature sensor, and the temperature evaluation result is obtained by identifying and analyzing the injection molding temperature information during the injection molding process; A control strategy is generated according to the temperature evaluation result, and the injection mold is injection-controlled during the injection molding process according to the control strategy.

[0035] Furthermore, in the injection molding electronics, the coolant performance degradation characteristic data of the cooling system under each operating frequency is obtained, and the cooling performance prediction model of the coolant is constructed according to the coolant performance degradation characteristic data of the cooling system under each operating frequency, specifically including: Acquire coolant performance degradation characteristic data of the cooling system at each operating frequency, and construct a cooling performance prediction model of the coolant based on a deep neural network, with the operating frequency as the first node and the coolant performance degradation characteristic data as the second node; Constructing a directed description relationship, connecting the first node and the second node based on the directed description relationship, constructing a topological structure graph, obtaining a related adjacency matrix based on the topological structure graph, and obtaining an adjacency matrix for each timestamp; The adjacency matrix of each timestamp is used as a state vector, and the transition probability value of the state vector to the next state vector is calculated. If the transition probability value is greater than the preset probability value, the current state vector is updated to the next state vector; If the transfer probability value is not greater than the preset probability value, the current state vector is maintained unchanged, the processed state vector is obtained, and a state vector matrix based on a time series is constructed. The state vector matrix based on a time series is input into the cooling performance prediction model of the coolant for training.

[0036] It should be noted that the coolant performance degradation characteristic data includes the temperature drop within a unit time, the temperature increase of the coolant within a unit time, the heat data taken away by the coolant within a unit time, etc. Among them, the actual state transfer is equivalent to a Markov model, and the transfer probability value of the state vector to the next state vector is calculated through the Markov chain. If the transfer probability value is greater than the preset probability value, the current state vector is updated to the next state vector. If the transfer probability value is not greater than the preset probability value, the current state vector is maintained unchanged, and the processed state vector is obtained to realize the update of the state, thereby improving the prediction accuracy of the coolant cooling performance prediction model.

[0037] Furthermore, in injection molding electronics, the state vector matrix based on the time series is input into the cooling performance prediction model of the coolant for training, specifically: A prediction accuracy threshold is set, and a state vector matrix based on the time series is input into the cooling performance prediction model of the coolant for training, so as to obtain the prediction accuracy of the cooling performance prediction model of the coolant; Determine whether the prediction accuracy of the cooling performance prediction model of the coolant is greater than a prediction accuracy threshold, and if so, the training of the cooling performance prediction model of the coolant is terminated; When the prediction accuracy of the cooling performance prediction model of the coolant is not greater than the prediction accuracy threshold, the cooling performance prediction model of the coolant is continuously trained until it is greater than the prediction accuracy threshold.

[0038] Furthermore, in the injection molding electronics, the cooling performance data of the coolant in the cooling system within a preset time is predicted according to the cooling performance prediction model of the coolant, specifically: Obtaining coolant performance change characteristic data within a preset time and operating frequency data within a preset time; Inputting the coolant performance change characteristic data within a preset time and the working frequency data within a preset time into the coolant cooling performance prediction model for prediction; Through prediction, the cooling performance data of the coolant in the cooling system within a preset time is obtained, and the cooling performance data of the coolant in the cooling system within the preset time is output.

[0039] Furthermore, in the injection molding electronics, the injection molding temperature information during the injection molding process is collected by a temperature sensor, and the injection molding temperature information during the injection molding process is identified and analyzed to obtain the temperature evaluation result, specifically: An injection temperature threshold is set, and injection temperature information during the injection molding process is collected through a temperature sensor to determine whether the injection temperature information during the injection molding process is greater than the injection temperature threshold; when the injection temperature information during the injection molding process is greater than the injection temperature threshold, the injection temperature information during the injection molding process is used as abnormal temperature information, and the abnormal temperature information is output as a temperature evaluation result.

[0040] When the injection temperature information during the injection molding process is not greater than the injection temperature threshold, the injection temperature information during the injection molding process is regarded as normal temperature information, and the normal temperature information is output as the temperature evaluation result.

[0041] It should be noted that this method can be used to evaluate whether the temperature is abnormal, thereby performing intelligent temperature control.

[0042] Furthermore, in the injection molding electronics, a control strategy is generated according to the temperature evaluation results and the cooling performance data of the coolant of the cooling system within a preset time, and the injection molding mold is injection-controlled during the injection molding process according to the control strategy, specifically: Acquire cooling demand information during the injection molding process. When the temperature evaluation result is abnormal temperature information, determine whether the cooling performance data of the coolant of the cooling system within a preset time is greater than the cooling demand information during the injection molding process; If it is greater than, the flow data of the coolant in the cooling system within a unit time is evenly increased again, and the cooling system is controlled according to the flow data of the coolant in the cooling system within a unit time; By controlling, the injection molding temperature information in the injection molding process within the preset time is continuously collected, and it is determined whether the injection molding temperature information in the injection molding process within the preset time is abnormal temperature information; When the injection temperature information during the injection molding process within the preset time is abnormal temperature information, the flow data of the coolant in the cooling system within the unit time is readjusted until it is no longer abnormal temperature information; When the injection temperature information during the injection molding process within the preset time is not abnormal temperature information, the cooling system is continuously controlled according to the flow data of the coolant within the unit time of the cooling system.

[0043] It should be noted that the injection molding temperature during the injection molding process can be accurately controlled by this method.

[0044] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0045] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0046] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0047] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: a mobile storage device, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0048] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0049] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. An injection mold, characterized in that: Specifically include: Injection mold body, A cooling system connected to the injection mold body, through which a coolant is provided and the injection temperature during the injection molding process is controlled by the coolant; Temperature sensor, responsible for obtaining injection temperature information during the injection molding process; The control system is responsible for controlling the flow data of the coolant in the cooling system within a unit time according to the injection temperature information during the injection molding process.

2. An injection molding method, characterized in that: An injection mold according to claim 1, comprising the following steps: Acquiring coolant performance degradation characteristic data of the cooling system at each operating frequency, and constructing a cooling performance prediction model of the coolant according to the coolant performance degradation characteristic data of the cooling system at each operating frequency; Predicting the cooling performance data of the coolant in the cooling system within a preset time according to the cooling performance prediction model of the coolant; The injection molding temperature information during the injection molding process is collected through the temperature sensor, and the temperature evaluation result is obtained by identifying and analyzing the injection molding temperature information during the injection molding process; A control strategy is generated according to the temperature evaluation result and the cooling performance data of the coolant of the cooling system within a preset time, and the injection mold is injection-controlled during the injection molding process according to the control strategy.

3. An injection molding method according to claim 1, characterized in that: Acquiring coolant performance degradation characteristic data of the cooling system at each operating frequency, and constructing a cooling performance prediction model of the coolant according to the coolant performance degradation characteristic data of the cooling system at each operating frequency, specifically including: Acquire coolant performance degradation characteristic data of the cooling system at each operating frequency, and construct a cooling performance prediction model of the coolant based on a deep neural network, with the operating frequency as the first node and the coolant performance degradation characteristic data as the second node; Constructing a directed description relationship, connecting the first node and the second node based on the directed description relationship, constructing a topological structure graph, obtaining a related adjacency matrix based on the topological structure graph, and obtaining an adjacency matrix for each timestamp; Taking the adjacency matrix of each timestamp as a state vector, calculating the transition probability value of the state vector to the next state vector, and if the transition probability value is greater than a preset probability value, updating the current state vector to the next state vector; If the transfer probability value is not greater than the preset probability value, the current state vector is maintained unchanged, the processed state vector is obtained, and a state vector matrix based on a time series is constructed. The state vector matrix based on a time series is input into the cooling performance prediction model of the coolant for training.

4. An injection molding method according to claim 3, characterized in that: The state vector matrix based on the time series is input into the cooling performance prediction model of the coolant for training, specifically: Setting a prediction accuracy threshold, inputting the time series-based state vector matrix into the cooling performance prediction model of the coolant for training, and obtaining the prediction accuracy of the cooling performance prediction model of the coolant; Determine whether the prediction accuracy of the cooling performance prediction model of the coolant is greater than the prediction accuracy threshold, and if so, the training of the cooling performance prediction model of the coolant is terminated; When the prediction accuracy of the cooling performance prediction model of the coolant is not greater than the prediction accuracy threshold, the cooling performance prediction model of the coolant is continuously trained until it is greater than the prediction accuracy threshold.

5. An injection molding method according to claim 1, characterized in that: The cooling performance prediction model of the coolant is used to predict the cooling performance data of the coolant in the cooling system within a preset time, specifically: Obtaining coolant performance change characteristic data within a preset time and operating frequency data within a preset time; Inputting the coolant performance change characteristic data within the preset time and the operating frequency data within the preset time into the coolant cooling performance prediction model for prediction; By prediction, the cooling performance data of the coolant in the cooling system within a preset time is obtained, and the cooling performance data of the coolant in the cooling system within the preset time is output.

6. An injection molding method according to claim 1, characterized in that: The injection temperature information during the injection molding process is collected by the temperature sensor, and the temperature evaluation results are obtained by identifying and analyzing the injection temperature information during the injection molding process, specifically: Setting an injection temperature threshold, and collecting injection temperature information during the injection molding process through a temperature sensor, and determining whether the injection temperature information during the injection molding process is greater than the injection temperature threshold; When the injection molding temperature information during the injection molding process is greater than the injection molding temperature threshold, the injection molding temperature information during the injection molding process is used as abnormal temperature information, and the abnormal temperature information is output as a temperature evaluation result; When the injection temperature information during the injection molding process is not greater than the injection temperature threshold, the injection temperature information during the injection molding process is used as normal temperature information, and the normal temperature information is output as a temperature evaluation result.

7. An injection molding method according to claim 1, characterized in that: A control strategy is generated according to the temperature evaluation result and the cooling performance data of the coolant of the cooling system within a preset time, and the injection mold is injection-controlled during the injection molding process according to the control strategy, specifically: Acquire cooling requirement information during the injection molding process, and when the temperature evaluation result is abnormal temperature information, determine whether the cooling performance data of the coolant of the cooling system within a preset time is greater than the cooling requirement information during the injection molding process; If it is greater than, then the flow data of the coolant in the cooling system within a unit time is uniformly increased again, and the cooling system is controlled according to the flow data of the coolant in the cooling system within a unit time; By controlling, the injection molding temperature information in the injection molding process within a preset time is continuously collected, and it is determined whether the injection molding temperature information in the injection molding process within the preset time is abnormal temperature information; When the injection temperature information during the injection molding process within the preset time is abnormal temperature information, the flow data of the coolant in the cooling system within the unit time is readjusted until it is no longer abnormal temperature information; When the injection temperature information during the injection molding process within the preset time is not abnormal temperature information, the cooling system is continuously controlled according to the flow data of the coolant within the unit time of the cooling system.

8. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory includes an injection molding method program, and when the injection molding method program is executed by the processor, the following steps are implemented: Acquiring coolant performance degradation characteristic data of the cooling system at each operating frequency, and constructing a cooling performance prediction model of the coolant according to the coolant performance degradation characteristic data of the cooling system at each operating frequency; Predicting the cooling performance data of the coolant in the cooling system within a preset time according to the cooling performance prediction model of the coolant; The injection molding temperature information during the injection molding process is collected through the temperature sensor, and the temperature evaluation result is obtained by identifying and analyzing the injection molding temperature information during the injection molding process; A control strategy is generated according to the temperature evaluation result, and injection control is performed on the injection mold during the injection molding process according to the control strategy.

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