Intelligent temperature control system of spiral runner efficient heat dissipation injection mold

Abstract

The invention discloses an intelligent temperature control system of a spiral runner efficient heat dissipation injection mold, and relates to the technical field of injection molding. The system comprises the following modules: a melt data adaptation optimization module, a pressure maintaining and temperature control suitability optimization module and a thermal response condition quantification and judgment module. According to the method, firstly, the injection molding melt injected into the injection mold is monitored to reflect the melt injection molding data adaptation condition of the melt injection molding and temperature control condition, then melt data adaptation optimization is conducted, then the adjustment amplitude of data in the pressure maintaining stage is judged, and corresponding pressure maintaining and temperature control adaptation optimization measures are taken; and finally, the thermal response condition of the mold cavity of the injection mold is quantified and judged in the circulation period, cooling heat dissipation temperature control adjustment is conducted according to the thermal response condition, the precision of intelligent temperature control of the injection mold is improved, and the problem that in the prior art, the temperature control precision of a temperature control system is reduced is solved.

Description

Technical Field

[0001] The present invention relates to the field of injection molding technology, and in particular to an intelligent temperature control system for an injection mold with a spiral flow channel and high-efficiency heat dissipation. Background Art

[0002] In order to precisely control the mold temperature, improve the quality and production efficiency of injection molded products, and extend the mold life, an intelligent temperature control system for an injection mold with a spiral flow channel structure is designed. The existing technology specifically includes a spiral flow channel structure, an intelligent temperature control device, a temperature monitoring and feedback system, an intelligent control algorithm, and a human-computer interaction interface. The spiral flow channel structure is used to design a spiral cooling channel (or heating channel) inside the mold, thereby increasing the contact area between the fluid and the mold, thereby enhancing fluid disturbance and improving heat exchange efficiency. The intelligent temperature control device includes a temperature sensor, a heater, a cooling device (such as a water system or a hot oil circulation system), and is equipped with a PLC (Programmable Logic Controller) or an embedded controller. The temperature monitoring and feedback system uses multiple temperature sensors distributed in key areas of the mold (such as the mold cavity and the flow channel inlet and outlet) to collect temperature data in real time and upload it to the control system. The intelligent control algorithm adopts the PID control algorithm (Proportional–Integral–Derivative Control The system automatically adjusts the temperature using a proportional-integral-derivative control algorithm or a fuzzy control algorithm. It can also connect to the Industrial Internet of Things (IIoT) for remote monitoring and predictive maintenance. The human-machine interface displays the current temperature status and set parameters, and supports alarms, data export, and historical analysis.

[0003] For example, the Chinese invention patent with publication number CN120190989A discloses an injection mold with an intelligent temperature control function, including: an upper mold and a lower mold, the upper mold is provided with an injection port, the lower mold is provided with an injection cavity, the injection port is connected to the injection cavity, and the interiors of the upper mold and the lower mold together constitute a temperature control device; a polygonal groove is provided in the lower mold, and several movable plates are provided in the polygonal groove, the movable plates are slidably connected to the polygonal groove, and a connecting rod is provided between the movable plate and the polygonal groove, and the connecting rod is a memory metal.

[0004] For example, the Chinese invention patent with announcement number: CN114953384B discloses an intelligent temperature control system for injection molds used in the production of television cover panels, which includes: a temperature detection unit for detecting the temperature information of the injection mold, processing the temperature information to obtain a temperature detection base and comparing it with the detection coefficient threshold, and sending the injection mold pouring temperature abnormality signal obtained after processing to the controller; an injection molding detection unit for receiving the injection mold pouring temperature abnormality signal sent by the controller, and detecting the temperature of the injection molding machine when it is working, and sending the obtained injection molding machine detection signal to the temperature control unit; the temperature control unit is used to control the abnormal temperature of the injection molding machine or the injection mold, wherein, when the temperature of the injection molding machine is controlled, the injection mold is kept warm during the control process, and the temperature detection base of the injection mold is monitored for a second time.

[0005] The above technology has at least the following technical problems: Although the essence of the spiral flow channel is an efficient and extended cooling path, it changes the flow mode of the coolant in the mold. By extending the coolant path and increasing the heat exchange area to improve the heat exchange efficiency, it is beneficial for the temperature of each part of the mold cavity to tend to be consistent and reduce the deformation caused by temperature difference. However, due to the long spiral path, the coolant gradually heats up in the long path, resulting in a large outlet temperature difference, which in turn leads to control lag and slow thermal response. As a result, the set temperature is not reached for a long time, and a steady-state error occurs. The control system is prone to continue to "catch up" with the set value during the adjustment process, which causes temperature fluctuations and a decrease in the temperature control accuracy of the temperature control system. Summary of the Invention

[0006] In order to solve the technical problem of reduced temperature control accuracy of the temperature control system in the prior art, an embodiment of the present invention provides an intelligent temperature control system for a spiral runner high-efficiency heat dissipation injection mold. The technical solution includes: a melt data adaptation optimization module, a holding pressure temperature control adaptability optimization module, and a thermal response quantification and judgment module; wherein the melt data adaptation optimization module is used to monitor the injection melt injected into the injection mold to reflect the melt injection data adaptation of the melt injection and temperature control conditions and perform melt data adaptation optimization to reduce the influence of the injection change of the injection melt on the melt temperature; the holding pressure temperature control adaptability optimization module is used to determine the adjustment amplitude of the holding pressure stage data and take corresponding holding pressure temperature control adaptability optimization measures to reduce the influence of the holding pressure stage on the required temperature of injection molding; the thermal response quantification and judgment module is used to quantify and determine the thermal response of the injection mold cavity within the cycle, and perform cooling and heat dissipation temperature control adjustment according to the thermal response to ensure the heat dissipation effect of the injection mold cavity.

[0007] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least: 1. First, the injection melt injected into the injection mold is monitored to reflect the melt injection data adaptation of the melt injection and temperature control conditions, and then the melt data adaptation optimization is performed to reduce the influence of the injection changes of the injection melt on the melt temperature, further ensuring the temperature control accuracy in the initial stage of injection molding, and then the adjustment amplitude of the holding pressure stage data is determined and corresponding holding pressure temperature control adaptability optimization measures are taken to reduce the influence of the holding pressure stage on the required temperature for injection molding, thereby improving the stability of the temperature control in the holding pressure stage, and finally, the thermal response of the mold cavity of the injection mold is quantified and determined within the cycle, and the cooling and heat dissipation temperature control is adjusted according to the thermal response to ensure the heat dissipation effect of the mold cavity of the injection mold, thereby improving the accuracy of the intelligent temperature control of the injection mold, and solving the problem of decreased temperature control accuracy of the temperature control system in the prior art.

[0008] 2. First, the injection melt data of the melt injected into the injection molding machine is obtained, and the injection melt data is compared with the corresponding reference melt data to obtain the corresponding median of the melt reference interval, thereby realizing automatic selection of the corresponding optimization measures. Then, based on the comparison results, corresponding optimization measures are taken to improve the stability of injection temperature control. Then, the gap between the melt temperature ratio and the injection speed ratio is quantified to obtain the melt temperature-injection speed gap, which measures the degree of adaptability between the melt temperature and the injection speed. Finally, if the melt temperature-injection speed gap is lower than the preset gap, no additional processing is performed. Otherwise, the corresponding melt temperature and the initial injection speed of injection molding are adjusted to the median of the melt temperature and the median of the injection speed, thereby improving the positive adaptability of the melt temperature and the initial injection speed of injection molding, thereby improving the stability and accuracy of temperature control in the initial stage of injection molding.

[0009] 3. Based on the injection molding standard, the injection speed in the initial stage of injection molding is adjusted to the injection speed in the later stage of injection molding, and the corresponding holding pressure in the cycle is obtained at the same time. The change amplitude of the injection speed and the change amplitude of the holding pressure in the later stage of injection molding in the cycle are obtained in real time. Then, the change amplitude of the injection speed in the later stage of injection molding and the change amplitude of the holding pressure are adaptively quantified to obtain the holding pressure control adaptation amount, which realizes the balance of the change amplitude between the injection speed and the holding pressure in the later stage of injection molding. Then, the holding pressure control adaptation amount and the set adaptation amount error range are judged and the corresponding maximum holding time limit is obtained based on the mold cavity temperature drop gradient mapping in the cycle. Finally, corresponding adjustments are made based on the corresponding judgment results, thereby ensuring the accuracy of mold cavity temperature control in the holding pressure stage, thereby improving the heat dissipation effect of the injection mold.

[0010] 4. The thermal response data of the spiral flow channel is obtained by the detection equipment deployed on the injection mold to obtain the thermal response determination coefficient, which realizes more accurate quantification of the thermal response of the spiral flow channel. Then, the thermal response determination coefficient is compared with the set thermal response determination range: if the thermal response determination coefficient belongs to the set thermal response determination range, it means that the thermal response is normal and no additional processing is performed. If the thermal response determination coefficient is lower than the minimum value of the set thermal response determination range, it means that the thermal response is too slow, and the first thermal response optimization measure is executed to reduce the impact of the slow thermal response on the cooling and heat dissipation of the injection molded product. If the thermal response determination coefficient is higher than the maximum value of the set thermal response determination range, it means that the thermal response is too fast, and the second thermal response optimization measure is executed to reduce the impact of the fast thermal response on the cooling and heat dissipation of the injection molded product, thereby improving the timeliness of the thermal response and promoting the improvement of the intelligent temperature control accuracy of the injection mold.

[0011] 5. If the thermal response determination coefficient of the next cycle after temperature control adjustment according to the thermal response situation belongs to the thermal response determination range, the spiral flow channel improvement suggestion will not be output and the waiting state will be maintained to prevent the spiral flow channel improvement suggestion from being misreported, thereby improving the robustness of the system. If the thermal response determination coefficient is still lower than the minimum value of the set thermal response determination range, the cooling water flow of the next cycle will be increased according to the increase amplitude used to initially increase the cooling water flow based on the first control ratio of the cooling water flow until the thermal response determination coefficient belongs to the set thermal response determination range, thereby ensuring the timeliness of the thermal response. If the number of cycles reaches the cycle limit, the optimization cycle will be stopped to prevent the system from falling into an infinite loop, and the corresponding spiral flow will be sent. The spiral flow channel improvement suggestions are sent to the staff terminal of the control system. If the thermal response determination coefficient is still higher than the maximum value of the set thermal response determination range, the cooling water flow of the next cycle is reduced according to the reduction amplitude used to initially reduce the cooling water flow based on the second control ratio of the cooling water flow, until the thermal response determination coefficient belongs to the set thermal response determination range, thereby improving the stability of the system thermal response. If the number of cycles reaches the cycle limit, the optimization cycle is stopped, and the corresponding spiral flow channel improvement suggestions are sent to the staff terminal of the control system, which provides a more effective measure to improve the thermal response of the injection mold, thereby ensuring the heat dissipation effect of the injection molding equipment, and further helping to improve the control accuracy of the injection mold intelligent temperature control system. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0013] Figure 1This is a structural schematic diagram of an intelligent temperature control system for an injection mold with a spiral flow channel and high-efficiency heat dissipation, provided by an embodiment of the present invention; Figure 2 1 is a schematic diagram of a process for melt data adaptation and optimization provided by an embodiment of the present invention; Figure 3 It is a schematic diagram of a process for quantifying and determining thermal response conditions provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0014] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0015] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as an "exemplary" in the present invention should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of the word "exemplary" is intended to present concepts in a concrete manner. Furthermore, in the embodiments of the present invention, "and / or" can mean both or either of the two.

[0016] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0017] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0018] The embodiment of the present invention provides an intelligent temperature control system for an injection mold with a spiral flow channel and high efficiency heat dissipation. Figure 1 The structure diagram of an intelligent temperature control system for a spiral runner efficient heat dissipation injection mold is shown. The processing flow of the system may include: a melt data adaptation optimization module, a pressure holding temperature control adaptability optimization module, and a thermal response quantification and judgment module.

[0019] Among them, the melt data adaptation optimization module is used to monitor the injection melt injected into the injection mold to reflect the melt injection data adaptation of the melt injection and temperature control conditions and perform melt data adaptation optimization to reduce the impact of the injection changes of the injection melt on the melt temperature.

[0020] The packing temperature adaptability optimization module is used to determine the adjustment range of the packing stage data and take corresponding packing temperature adaptability optimization measures to reduce the impact of the packing stage on the required temperature for injection molding.

[0021] The thermal response quantification and determination module is used to quantify and determine the thermal response of the injection mold cavity within a cycle, and to adjust the cooling and heat dissipation temperature control according to the thermal response to ensure the heat dissipation effect of the injection mold cavity.

[0022] In this embodiment, through the melt data adaptation optimization module, the system actively compensates and optimizes when the melt is injected, reducing the melt temperature changes caused by mechanical variables such as injection speed and pressure fluctuations. This is equivalent to ensuring that the "initial state" of the heat is more stable and consistent before entering the mold cavity, laying a solid foundation for subsequent precise cooling; then, through the pressure holding temperature control adaptability optimization module, the system more accurately manages the pressure holding stage, which has a great impact on the product size, shrinkage and internal stress. Pressure holding is not simply maintaining a temperature, but "adaptability optimization" is performed according to the adjustment of the pressure holding data, and it helps to prevent defects such as warping and shrinkage in the product. Finally, through the thermal response quantification and judgment module, the system performs closed-loop feedback control on the final heat dissipation effect to ensure that no matter what abnormalities occur in the front end (injection, pressure holding), the final heat dissipation effect of the mold cavity is always accurately maintained within the optimal range, thereby improving the temperature control accuracy of the injection mold intelligent temperature control system.

[0023] like Figure 2 As shown in FIG, it is a flow chart of melt data adaptation optimization provided by an embodiment of the present invention, and the specific logic is: obtain the injection melt data of the melt injected into the injection molding machine, compare the injection melt data with the corresponding reference melt data interval and obtain the corresponding melt reference interval median; if the melt temperature is less than the minimum value of the melt temperature reference interval, adjust the melt temperature to the minimum value of the melt temperature reference interval; if the melt temperature is greater than the maximum value of the melt temperature reference interval, adjust the melt temperature to the maximum value of the melt temperature reference interval; if the injection speed at the initial stage of injection molding is less than the minimum value of the injection speed interval at the initial stage of injection molding, adjust the injection speed at the initial stage of injection molding to the minimum value of the injection speed interval at the initial stage of injection molding; if the injection speed at the initial stage of injection molding is greater than the maximum value of the injection speed interval at the initial stage of injection molding, adjust the injection speed at the initial stage of injection molding to the minimum value of the injection speed interval at the initial stage of injection molding; The maximum value of the injection speed range is used, and the injection speed at the initial stage of injection molding is adjusted to the maximum value of the injection speed range at the initial stage of injection molding; if the injection melt data all belong to the reference melt data range, the proportion of each injection melt data in the corresponding reference melt data range is obtained, and the melt temperature proportion and injection speed proportion are obtained respectively; the difference between the melt temperature proportion and the injection speed proportion is quantified to obtain the melt temperature-injection speed difference that measures the adaptability difference between the melt temperature and the injection speed; if the melt temperature-injection speed difference is lower than the preset difference, no additional processing is performed, otherwise the corresponding melt temperature and injection speed at the initial stage of injection molding are adjusted to the median melt temperature and the median injection speed; through the above process, the robustness of the intelligent temperature control system and the accuracy of the injection mold temperature control are improved.

[0024] Furthermore, the injection melt injected into the injection mold is monitored to reflect the melt injection data adaptation of the melt injection and temperature control conditions and to perform melt data adaptation optimization. The specific process is as follows: First, injection melt data of the melt injected into the injection molding machine is acquired. The injection melt data includes melt temperature and injection speed at an initial stage of injection molding. The injection speed at an initial stage of injection molding represents an initial value of the injection speed at an initial stage of injection molding.

[0025] Specifically, the melt temperature is measured by a thermocouple deployed at the rear end of the screw. The initial injection speed represents the speed at the beginning of the injection process (which can be expressed as volume flow rate or linear speed) and is directly read through the injection molding machine control panel.

[0026] Next, the injection melt data is compared with the corresponding reference melt data interval to obtain the corresponding melt reference interval median, the reference melt data interval includes the melt temperature reference interval and the injection speed interval at the initial stage of injection molding, and the melt reference interval median includes the melt temperature median and the injection speed median.

[0027] It should be added that the reference melt data range is usually pre-set by the preset staff based on the injection molding production requirements and historical data experience, and stored in a pre-set database, which can be directly extracted when used; the median of the melt reference range is the median of the melt temperature reference range and the initial injection speed range.

[0028] If the melt temperature is less than the minimum value of the melt temperature reference interval, the melt temperature is adjusted to the minimum value of the melt temperature reference interval. If the melt temperature is greater than the maximum value of the melt temperature reference interval, the melt temperature is adjusted to the maximum value of the melt temperature reference interval.

[0029] If the initial injection speed is less than the minimum value of the initial injection speed range, the initial injection speed is adjusted to the minimum value of the initial injection speed range; if the initial injection speed is greater than the maximum value of the initial injection speed range, the initial injection speed is adjusted to the maximum value of the initial injection speed range.

[0030] If the injection melt data all belong to the corresponding reference melt data interval, then obtain the proportion of each injection melt data in the corresponding reference melt data interval, and obtain the melt temperature proportion and injection speed proportion respectively. The melt temperature proportion is used to quantify the data distribution of the melt temperature in the melt temperature reference interval, and the injection speed proportion is used to quantify the data distribution of the injection speed in the initial injection molding period in the injection speed interval.

[0031] Specifically, the absolute value of the difference between the melt temperature and the minimum value of the melt temperature reference interval is ratioed to the absolute value of the difference between the minimum value of the melt temperature reference interval and the maximum value of the melt temperature reference interval to obtain the melt temperature proportion, and the absolute value of the difference between the initial injection speed and the minimum value of the initial injection speed interval is ratioed to the absolute value of the difference between the minimum value of the initial injection speed interval and the maximum value of the initial injection speed interval to obtain the injection speed proportion.

[0032] Then, the gap between the melt temperature ratio and the injection speed ratio is quantified to obtain the melt temperature-injection speed gap, which measures the adaptability difference between the melt temperature and the injection speed; the gap quantification means performing the difference operation between the melt temperature ratio and the injection speed ratio and then taking the absolute value.

[0033] Finally, if the melt temperature-injection speed gap is lower than the preset gap, no additional processing is performed. Otherwise, the corresponding melt temperature and initial injection speed of injection molding are adjusted to the median melt temperature and the median injection speed. The preset gap is pre-set by the preset staff based on the positive adaptation degree of the melt temperature and the initial injection speed in historical data experience.

[0034] In this embodiment, by real-time monitoring of the melt temperature and injection speed and comparing them with the preset reference range, it helps to ensure that the key process parameters are always within a reasonable range, avoiding molding defects caused by parameter out-of-limit (such as short shots, flash, burning, etc.), and at the same time, by calculating the melt temperature ratio and the injection speed ratio, the distribution position of the parameters in the reference range is quantified to avoid the situation where the parameters are within the range but tend to extreme values ​​(such as the temperature is close to the upper limit and the speed is close to the lower limit); and when the parameter adaptability does not meet the requirements (the gap exceeds the limit), it automatically returns to the median of the interval (the median of the melt temperature and the median of the injection speed), and uses the middle data as a fault-tolerant solution, reducing the need for human intervention and improving the accuracy of the intelligent temperature control system in controlling the temperature of the injection mold.

[0035] Furthermore, the adjustment range of the pressure holding stage data is determined and corresponding pressure holding temperature control adaptability optimization measures are taken. The specific process is as follows: H1, based on the injection molding standard, adjusts the injection speed at the initial stage of injection molding to the injection speed at the later stage of injection molding, and obtains the corresponding holding pressure within the cycle, and obtains the change range of the injection speed and the holding pressure at the later stage of injection molding within the cycle in real time.

[0036] It should be explained that the injection molding standard indicates that the injection speed at the initial stage of injection molding needs to be adjusted to the pressure-holding reference injection speed range to obtain the injection speed at the later stage of injection molding. The pressure-holding reference injection speed range is the reference range corresponding to the injection speed in the pressure-holding stage, which is pre-set by the preset staff. The pressure-holding stage usually refers to slow pressure holding. The injection speed should be gradually reduced and eventually approach zero to ensure smooth melt flow during mold filling. At the same time, the holding pressure in the mold should quickly and smoothly reach the set value and be maintained within a stable range. If the pressure-holding process is well controlled, it can ensure that the melt is filled in the mold and the air is effectively expelled. The corresponding holding pressure can be obtained through the cavity pressure sensor (embedded in the mold).

[0037] In addition, the late injection speed change amplitude represents the value obtained by performing a difference calculation between the late injection speed in the current cycle and the late injection speed in the previous cycle, and then performing a ratio calculation with the late injection speed in the previous cycle. For example, if the late injection speed in the current cycle decreases by 10% compared with the late injection speed in the previous cycle, the late injection speed change amplitude is -10%. Similarly, the holding pressure change amplitude represents the value obtained by performing a difference calculation between the holding pressure in the current cycle and the holding pressure in the previous cycle, and then performing a ratio calculation with the holding pressure in the previous cycle. For example, if the holding pressure in the current cycle increases by 15% compared with the holding pressure in the previous cycle, the holding pressure change amplitude is 15%.

[0038] H2, quantify the adaptability of the injection speed change amplitude and the holding pressure change amplitude in the late injection molding process, that is, add the injection speed change amplitude and the holding pressure change amplitude in the late injection molding process to obtain the holding pressure control adaptation amount that measures the balance of the change amplitude between the injection speed and the holding pressure in the late injection molding process.

[0039] H3, the holding pressure control adaptation amount and the set adaptation amount error range are judged and the corresponding maximum holding time limit is obtained based on the mold cavity temperature drop gradient mapping within the cycle period. If the holding pressure control adaptation amount belongs to the adaptation amount error range, the corresponding holding pressure time is obtained based on the holding pressure control adaptation amount mapping. If the holding pressure time is lower than the maximum holding pressure time limit, the injection molding melt continues to be held based on the holding pressure time; otherwise, the injection molding melt continues to be held based on the maximum holding pressure time limit.

[0040] Specifically, the adaptation amount error interval is a range set by the preset staff based on the principle of slow pressure holding to maintain a balance between the adjustment amplitude of the pressure holding pressure and the subsequent injection speed.

[0041] It should be added that the holding time mapping table is a data table set in advance in a preset database for fitting the mapping relationship between the holding pressure control adaptation amount and the holding pressure time. In the holding pressure time mapping table, there is a one-to-one or many-to-one mapping relationship between the holding pressure control adaptation amount and the holding pressure time. The obtained holding pressure control adaptation amount is queried in the first holding pressure time mapping table to obtain the holding pressure time with which there is a mapping relationship.

[0042] It should be explained that the cavity temperature drop gradient represents the ratio of the difference between the cavity temperature of the current cycle and the cavity temperature of the previous cycle to the cavity temperature of the previous cycle. The cavity temperature drop gradient is input into the holding time limit mapping table, and the maximum holding time limit with which there is a one-to-one or many-to-one mapping relationship is output. The holding time limit mapping table is used to fit the mapping relationship between the cavity temperature drop gradient and the maximum holding time limit.

[0043] H4, if the holding pressure control adaptation amount is less than the minimum value of the adaptation amount error interval, then the injection speed reduction control rate influence amount and the holding pressure time influence amount are mapped based on the difference between the holding pressure control adaptation amount and the minimum value of the adaptation amount error interval, and the corresponding injection speed reduction rate is controlled based on the injection speed reduction control rate influence amount, that is, the injection speed reduction control rate influence amount is multiplied by the initial reduction rate of the injection speed reduction rate to obtain the corresponding optimized injection speed reduction rate, and the injection speed reduction rate is increased accordingly, and the optimized holding pressure time is obtained based on the holding pressure time influence amount and the initial holding pressure time, which means that the sum of the holding pressure time influence amount and data 1 is multiplied by the initial holding pressure time to obtain the optimized holding pressure time. If the optimized holding pressure time is lower than the maximum holding pressure time limit, the injection molding melt continues to be pressurized based on the optimized holding pressure time, otherwise the injection molding melt continues to be pressurized based on the maximum holding pressure time limit.

[0044] It needs to be explained that the difference between the adaptive amount of holding pressure control and the minimum value of the adaptive amount error interval is recorded as the first adaptive amount error. There is an adaptive amount first error mapping data set associated with the first adaptive amount error in the preset database. This data set is used to simulate the mapping relationship between the first adaptive amount error and the first adaptive amount data group, that is, the first adaptive amount error is input into the adaptive amount first error mapping data set, and the first adaptive amount data group can be output. The first adaptive amount data group includes the injection speed drop control rate influence amount and the holding pressure time influence amount.

[0045] H5, if the holding pressure control adaptation amount is greater than the maximum value of the adaptation amount error interval, then the difference between the holding pressure control adaptation amount and the maximum value of the adaptation amount error interval is mapped to obtain the holding pressure rise control rate influence amount and the holding pressure time influence amount, and the corresponding holding pressure rise speed is controlled based on the holding pressure rise control rate influence amount, that is, the holding pressure rise control rate influence amount is multiplied by the initial rising speed of the holding pressure rise speed to obtain the corresponding optimized holding pressure rise speed, and the holding pressure rise speed is reduced accordingly, and the optimized holding time is obtained by processing based on the holding time influence amount and the initial holding time, which means that the sum of the holding time influence amount and data 1 is multiplied by the initial holding time to obtain the optimized holding time. If the optimized holding time is lower than the maximum holding time limit, the injection molding melt continues to be pressurized based on the optimized holding time, otherwise the injection molding melt continues to be pressurized based on the maximum holding time limit.

[0046] It needs to be explained that the difference between the adaptive amount of the pressure holding control and the maximum value of the adaptive amount error interval is recorded as the adaptive amount second error. There is an adaptive amount second error mapping data set associated with the adaptive amount second error in the preset database. This data set is used to simulate the mapping relationship between the adaptive amount second error and the second adaptive amount data group, that is, the adaptive amount second error is input into the adaptive amount second error mapping data set, and the second adaptive amount data group can be output. The second adaptive amount data group includes the holding pressure rise control rate influence amount and the holding pressure time influence amount.

[0047] In this embodiment, by real-time monitoring of the injection speed change amplitude and the holding pressure change amplitude in the late stage of injection molding, and quantifying the adaptability (holding pressure control adaptation amount), it is ensured that the coordinated changes in speed and pressure meet the process requirements, and avoid defects such as shrinkage and warping caused by imbalance between the two; and the introduction of the maximum limit of the holding time of the mold cavity temperature drop gradient mapping helps to avoid uneven cooling or decreased production efficiency due to too long holding time; at the same time, the injection speed is reduced by controlling the rate influence amount through the injection speed drop, and the holding time is adjusted at the same time, thereby alleviating the problem of insufficient pressure caused by excessive injection speed.

[0048] like Figure 3As shown, it is a flow chart of the quantification and determination of the thermal response provided by an embodiment of the present invention, and the specific logic is: step one, obtaining the thermal response data of the spiral flow channel by means of the detection equipment deployed on the injection mold to obtain the thermal response determination coefficient; step two, comparing the thermal response determination coefficient with the set thermal response determination range: if the thermal response determination coefficient belongs to the set thermal response determination range, no additional processing is performed; if the thermal response determination coefficient is lower than the minimum value of the set thermal response determination range, the first thermal response optimization measure is executed; if the thermal response determination coefficient is higher than the maximum value of the set thermal response determination range, the second thermal response optimization measure is executed; wherein, the specific content of the first thermal response optimization measure is as follows: obtaining the median value of the thermal response determination range, and performing differential quantification on the difference between the median value and the thermal response determination coefficient to obtain the first ideal thermal response compensation value, and at the same time performing differential quantification on the minimum value of the thermal response determination range and the thermal response determination coefficient to obtain the first minimum thermal response compensation value; comparing the first minimum thermal response compensation value with the first ideal thermal response The first minimum compensation ratio of thermal response is obtained by comparing the compensation values; the first control ratio of cooling water flow is obtained based on the projection of the first minimum compensation ratio of thermal response, and the cooling water flow in the spiral flow channel is increased according to the first control ratio of cooling water flow; in addition, the specific content of the second optimization measure of thermal response is as follows: the median of the thermal response judgment range is obtained, and the difference is quantified with the thermal response judgment coefficient to obtain the second ideal compensation value of thermal response, and the difference between the maximum value of the thermal response judgment range and the thermal response judgment coefficient is obtained to obtain the second minimum compensation value of thermal response; the second minimum compensation value of thermal response is compared with the second ideal compensation value of thermal response to obtain the second minimum compensation ratio of thermal response; the second control ratio of cooling water flow is obtained based on the projection of the second minimum compensation ratio of thermal response, and the cooling water flow in the spiral flow channel is reduced according to the second control ratio of cooling water flow; the above process helps to more accurately quantify the thermal response of the spiral flow channel, improves the timeliness of the thermal response, and improves the accuracy of intelligent temperature control of the injection mold.

[0049] Furthermore, the thermal response of the mold cavity of the injection mold is quantified and determined during the cycle. The specific steps are as follows: Step 1: Obtain the thermal response data of the spiral flow channel through the detection equipment deployed in the injection mold to obtain the thermal response determination coefficient used to quantify the thermal response of the spiral flow channel. The thermal response data includes temperature adjustment time, temperature overshoot value, temperature callback time, temperature stabilization error and thermal lag time. The detection equipment includes thermocouples, temperature probes and flow sensors.

[0050] Through multi-dimensional detection equipment such as thermocouples, temperature probes, flow sensors, etc., key parameters such as the temperature adjustment time, temperature overshoot value, temperature callback time, temperature stabilization error, thermal lag time, etc. of the spiral flow channel are collected in real time, which helps to comprehensively calculate the thermal response determination coefficient and more scientifically evaluate the thermal dynamic characteristics of the mold cavity.

[0051] Specifically, the temperature adjustment time indicates the time taken from the start of system adjustment (heating / cooling) to reaching the set temperature, the temperature overshoot value indicates the maximum deviation when the temperature first exceeds the set value, the temperature callback time indicates the time taken to fall back from the overshoot and stabilize within the set temperature range, the temperature stabilization error indicates the deviation between the system and the target temperature in steady state, and the thermal lag time indicates the delay time for the actual temperature to start responding after the control signal changes. The above data is read from the PID controller interface.

[0052] Step 2: Compare the thermal response determination coefficient with the set thermal response determination range. Through real-time comparison of the thermal response determination coefficient and the thermal response determination range, abnormal thermal responses (such as temperature overshoot or lag) can be quickly identified, reducing the trial mold adjustment time.

[0053] If the thermal response determination coefficient falls within the set thermal response determination range, it means that the thermal response is normal and no additional processing is performed.

[0054] If the thermal response determination coefficient is lower than the minimum value of the set thermal response determination range, it means that the thermal response is too slow, and the first thermal response optimization measure is executed to reduce the impact of the slow thermal response on the cooling and heat dissipation of the injection molded product.

[0055] If the thermal response determination coefficient is higher than the maximum value of the set thermal response determination range, it means that the thermal response is too fast, and the second thermal response optimization measure is executed to reduce the impact of the fast thermal response on the cooling and heat dissipation of the injection molded product.

[0056] It needs to be explained that the thermal response judgment range is obtained from a preset database. Based on experience, the preset staff substitutes the thermal response data corresponding to the slow thermal response in the historical data into the specific restriction expression of the thermal response judgment coefficient to obtain a data set about the slow thermal response. The data set is averaged to obtain the minimum value of the thermal response judgment range. Similarly, the thermal response data corresponding to the fast thermal response in the historical data is substituted into the specific restriction expression of the thermal response judgment coefficient to obtain a data set about the fast thermal response. The data set is averaged to obtain the maximum value of the thermal response judgment range. The range corresponding to the minimum value of the thermal response judgment range and the maximum value of the thermal response judgment range is the thermal response judgment range.

[0057] It should be added that the specific content of the first optimization measure for thermal response is as follows: A1, obtains the median of the thermal response judgment range, and performs differential quantization on it with the thermal response judgment coefficient to obtain the first ideal thermal response compensation value, that is, performs a difference operation on the median of the thermal response judgment range and the thermal response judgment coefficient to obtain the first ideal thermal response compensation value, and at the same time performs a differential quantization on the minimum value of the thermal response judgment range and the thermal response judgment coefficient to obtain the first minimum thermal response compensation value, which means that the first minimum thermal response compensation value is obtained by performing a subtraction operation on the minimum value of the thermal response judgment range and the thermal response judgment coefficient, and sets the compensation lower limit to prevent invalid adjustment caused by small fluctuations.

[0058] A2, comparing the first minimum thermal response compensation value with the first ideal thermal response compensation value to obtain a first minimum thermal response compensation ratio, that is, performing a ratio operation between the first minimum thermal response compensation value and the first ideal thermal response compensation value to obtain the first minimum thermal response compensation ratio.

[0059] A3, based on the projection of the first minimum compensation ratio of the thermal response, obtains the first control ratio of the cooling water flow, increases the cooling water flow in the spiral flow channel according to the first control ratio of the cooling water flow, that is, multiplies the first control ratio of the cooling water flow by the current cooling water flow to obtain the first controlled cooling water flow, and controls the cooling water flow accordingly.

[0060] It should be explained that the first minimum thermal response compensation ratio is input into the trained projection sequence to output the corresponding first cooling water flow control ratio, that is, the ratio of the first minimum thermal response compensation ratio to the cooling water flow that needs to be controlled. The training data used in this projection sequence comes from the first minimum thermal response compensation ratio obtained in a historical period, as well as the first cooling water flow control ratio set by professional technicians based on empirical rules. It is used to fit the mapping relationship between the first minimum thermal response compensation ratio and the first cooling water flow control ratio, thereby more accurately controlling the cooling water flow.

[0061] It should be added that the specific content of the second optimization measure for thermal response is as follows: B1, obtains the median of the thermal response judgment range, and quantifies the difference with the thermal response judgment coefficient to obtain the second ideal compensation value of the thermal response, which means that the median of the thermal response judgment range and the thermal response judgment coefficient are differenced to obtain the second ideal compensation value of the thermal response, and at the same time, the difference between the maximum value of the thermal response judgment range and the thermal response judgment coefficient is obtained to obtain the second minimum compensation value of the thermal response, that is, the maximum value of the thermal response judgment range and the thermal response judgment coefficient are subtracted to obtain the difference, and the difference is the second minimum compensation value of the thermal response; a dual-threshold compensation strategy is adopted, and the ideal compensation value based on the median and the minimum compensation value based on the maximum value are calculated at the same time, providing a more accurate reference range for regulation.

[0062] B2, comparing the second minimum thermal response compensation value with the second ideal thermal response compensation value to obtain the second minimum thermal response compensation ratio, that is, performing a ratio operation on the second minimum thermal response compensation value and the second ideal thermal response compensation value to obtain the second minimum thermal response compensation ratio.

[0063] B3, based on the projection of the second minimum compensation ratio of the thermal response, the second control ratio of the cooling water flow is obtained, and the cooling water flow in the spiral flow channel is reduced according to the second control ratio of the cooling water flow, that is, the second control ratio of the cooling water flow is multiplied by the current cooling water flow to obtain the second controlled cooling water flow, and the cooling water flow is controlled accordingly.

[0064] It should be explained that the second minimum compensation ratio for thermal response is input into the trained projection sequence to output the corresponding second control ratio for cooling water flow, that is, the ratio of the second minimum compensation ratio for thermal response to the cooling water flow that needs to be controlled. The training data used in this projection sequence comes from the second minimum compensation ratio for thermal response obtained during a historical period, as well as the second control ratio for cooling water flow set by professional technicians based on empirical rules. This is used to fit the mapping relationship between the second minimum compensation ratio for thermal response and the second control ratio for cooling water flow, thereby more accurately controlling the cooling water flow.

[0065] In this embodiment, by implementing the first thermal response optimization measure (such as increasing the coolant flow rate, optimizing the cooling water channel layout, or adjusting the mold temperature controller parameters), heat exchange is accelerated, which helps prevent product deformation or cycle extension due to insufficient heat dissipation. By implementing the second thermal response optimization measure (such as reducing the cooling rate, adjusting the mold temperature, or using gradient cooling), internal stress or surface defects (such as weld marks and shrinkage marks) caused by uneven cooling are avoided. At the same time, through real-time comparison of the thermal response determination coefficient and the thermal response determination range, abnormal thermal responses (such as temperature overshoot or lag) are quickly identified, thereby reducing the trial mold adjustment time and improving the timeliness of the thermal response.

[0066] As a further embodiment, the specific method of obtaining the thermal response determination coefficient is as follows: In the first step, the temperature overshoot value is proportionally quantified with the maximum overshoot value to obtain the corresponding temperature overshoot index. The proportional quantization is used to quantify the degree to which the temperature overshoot value deviates from the maximum overshoot value, wherein the proportional quantization means performing a ratio operation on the temperature overshoot value and the maximum overshoot value.

[0067] In the second step, the temperature adjustment time, temperature callback time, temperature stabilization error and thermal lag time are normalized and then logically fitted to obtain the corresponding temperature adjustment time index, temperature callback time index, temperature stabilization error index and thermal lag time index respectively. Among them, logical fitting is used to perform inverse proportional operation on the temperature adjustment time, temperature callback time, temperature stabilization error and thermal lag time, thereby ensuring a negative correlation with the thermal response determination coefficient.

[0068] In the third step, based on the temperature adjustment time index, temperature callback time index, temperature stability error index, thermal lag time index and temperature overshoot index, a weighted operation is performed with the corresponding thermal response analysis proportion to obtain the thermal response determination coefficient. The thermal response analysis proportion includes the temperature adjustment time analysis proportion, the temperature overshoot value analysis proportion, the temperature callback time analysis proportion, the temperature stability error analysis proportion and the thermal lag time analysis proportion.

[0069] It should be explained that thermal response data is input into a trained projection sequence to output the corresponding thermal response analysis weight, that is, the degree of influence of the thermal response data on the thermal response determination coefficient. The training data used in this projection sequence comes from thermal response data collected during a historical period, and the thermal response analysis weights set by professional technicians based on empirical rules. This is used to fit the mapping relationship between thermal response data and thermal response analysis weights, thereby providing a more accurate analysis of the thermal response determination coefficient.

[0070] The specific limiting expression of the thermal response determination coefficient is as follows: ; Where a represents the temperature adjustment time, b represents the temperature overshoot value, c represents the temperature callback time, d represents the temperature stabilization error, f represents the thermal hysteresis time, b0 represents the overshoot maximum value, γ a Indicates the analysis ratio of temperature adjustment time, γ b Indicates the analysis ratio of temperature overshoot value, γ c Indicates the analysis ratio of temperature callback time, γ d Indicates the temperature stability error analysis ratio, γ f represents the thermal hysteresis time analysis ratio, and ρ represents the thermal response determination coefficient.

[0071] In this embodiment, the algorithm combines thermal response data, overshoot maximum value and thermal response analysis ratio for comprehensive analysis to obtain the thermal response determination coefficient. In the formula, as the temperature adjustment time, temperature callback time, temperature stabilization error and thermal hysteresis time increase, the corresponding thermal response determination coefficient becomes smaller. The extended temperature adjustment time means that the time required to cool to the set temperature is longer than normal. For example, the cooling system originally reached the set temperature within 10 minutes, but it actually took 20 minutes, resulting in a slower thermal response. The flow change and thermal inertia in the spiral structure are large, making it impossible for the adjustment action to respond quickly to the target temperature, causing the temperature to exceed the set target during the adjustment process. The longer the temperature goes from overshoot to stable temperature, the slower the system response. In addition, the cooling water flow is affected by the spiral flow channel structure, which causes the cooling effect at certain positions to lag, and the temperature difference reaction is delayed, resulting in a slower thermal response. In summary, the smaller the corresponding thermal response determination coefficient is, the smaller the thermal response determination coefficient is. The analysis of the thermal response determination coefficient can help to more accurately quantify the thermal response of the current cycle, and make timely and automatic selection of the corresponding optimization measures based on the thermal response determination coefficient, thereby improving the timeliness of the thermal response and thus improving the accuracy of temperature control by the intelligent temperature control system.

[0072] Furthermore, the thermal response determination coefficient is compared with the set thermal response determination range, and suggestions for improving the spiral flow channel are output; On the one hand, if the first thermal response optimization measure is executed, the recommended increase in the number of spiral turns is obtained by querying the mapping table based on the first ideal thermal response compensation value, and waits for output to the staff terminal of the control system.

[0073] It should be added that there is a thermal response first spiral turn recommended mapping table in the preset database, which is used to fit the mapping relationship between the thermal response first ideal compensation value and the recommended increase in the number of spiral turns. The obtained thermal response first ideal compensation value is input into the thermal response first spiral turn recommended mapping table, and the corresponding recommended increase in the number of spiral turns is output.

[0074] On the other hand, if the second thermal response optimization measure is executed, the recommended reduction in the number of spiral turns is obtained by querying the mapping table based on the second ideal thermal response compensation value, and waits for output to the staff terminal of the control system.

[0075] It should be added that there is a thermal response second spiral turn recommended mapping table in the preset database, which is used to fit the mapping relationship between the thermal response second ideal compensation value and the recommended reduction in the number of spiral turns. The obtained thermal response second ideal compensation value is input into the thermal response second spiral turn recommended mapping table, and the corresponding recommended reduction in the number of spiral turns is output.

[0076] In this embodiment, a quantitative mapping relationship between the thermal response compensation value and the spiral flow channel structure adjustment is established to achieve a complete closed loop from parameter monitoring to modification suggestions. In addition, the digital encapsulation of knowledge and experience is achieved through a preset mapping table, reducing the dependence on operator experience. At the same time, the "system suggestion + manual confirmation" execution method is adopted to ensure professionalism while retaining room for manual judgment. Suggestions are output through the staff terminal, realizing workshop-level production process optimization. By intelligently associating real-time process data with flow channel structure parameters, a complete closed loop from process monitoring to injection mold improvement is achieved, which not only solves the current injection molding production problems, but also provides data support for long-term process optimization.

[0077] Furthermore, the cooling and heat dissipation temperature control is adjusted, and then the change trend adjustment is also included. Specifically, there are three situations: In the first case, if the thermal response determination coefficient of the next cycle after temperature control adjustment according to the thermal response situation falls within the thermal response determination range, no spiral flow channel improvement suggestion is output and the waiting state is maintained.

[0078] In the second case, if the thermal response determination coefficient is still lower than the minimum value of the set thermal response determination range, the cooling water flow of the next cycle is increased according to the increase amplitude used to increase the cooling water flow based on the first cooling water flow control ratio, that is, the increase amplitude is added to the first cooling water flow control ratio to obtain the optimized cooling water flow first control ratio, and the next cooling water flow is increased accordingly until the thermal response determination coefficient belongs to the set thermal response determination range. If the number of cycles reaches the cycle limit, the optimization cycle is stopped, and the corresponding spiral flow channel improvement suggestions are sent to the staff terminal of the control system.

[0079] In the third case, if the thermal response determination coefficient is still higher than the maximum value of the set thermal response determination range, the cooling water flow of the next cycle is reduced according to the reduction amplitude used to reduce the cooling water flow based on the second control ratio of the cooling water flow, that is, the reduction amplitude is subtracted from the second control ratio of the cooling water flow to obtain the optimized second control ratio of the cooling water flow, and the next cooling water flow is reduced accordingly until the thermal response determination coefficient belongs to the set thermal response determination range. If the number of cycles reaches the cycle limit, the optimization cycle is stopped, and the corresponding spiral flow channel improvement suggestions are sent to the staff terminal of the control system.

[0080] It should be added that the increase amplitude, decrease amplitude and cycle limit number are all obtained from the preset database. The increase amplitude is a fixed ratio set for increasing the first control ratio of the cooling water flow, the decrease amplitude is a fixed ratio set for reducing the second control ratio of the cooling water flow, and the cycle limit number is a limit value used to prevent the optimization sequence from falling into an infinite loop.

[0081] In this embodiment, precise temperature control is achieved by adopting a multi-cycle progressive adjustment strategy and then using a closed-loop control method of "evaluation-fine-tuning-re-evaluation". Each adjustment only adjusts the flow rate according to the initial ratio to avoid process fluctuations caused by over-adjustment. At the same time, this mechanism achieves dual guarantees, including both the short-term guarantee of immediate process optimization through dynamic flow adjustment and the long-term guarantee of triggering mold modification suggestions when multiple adjustments are ineffective. In addition, setting a cycle limit (such as 5-10 times) also balances adjustment efficiency and system stability, preventing the optimization cycle from falling into an infinite loop. In addition, by judging the trend of thermal response changes through continuous cycle data, problems requiring mold-level improvement are automatically identified, providing a decision-making basis for preventive maintenance of injection molds.

[0082] Furthermore, the change trend adjustment also includes: after each optimization cycle, obtaining the thermal response determination coefficient of the corresponding cycle, and quantifying the difference with the thermal response determination coefficient of the previous cycle to obtain the difference in cycle coefficients, that is, performing a difference operation on the thermal response determination coefficient of the current cycle and the thermal response determination coefficient of the previous cycle to obtain the difference in cycle coefficients. If the difference in cycle coefficients is greater than the set difference, the cycle processing continues; if the difference in cycle coefficients is not greater than the set difference, the cycle is stopped and the corresponding spiral flow channel improvement suggestion is sent to the staff terminal of the control system; wherein, the set difference refers to the data set by the preset staff for determining the eligibility of the progress of each optimization cycle effect.

[0083] In this embodiment, by quantifying the difference in circulation coefficients of adjacent cycles, a more scientifically optimized termination condition is established, and the process automatically stops when the adjustment effect tends to be flat (difference in circulation coefficients < set difference), thereby avoiding more invalid adjustments. The process constitutes a complete closed-loop optimization system of "adjustment-feedback-readjustment", which can continuously perform fine-tuning according to the actual operating results to ensure that the spiral flow channel always operates in a state close to the optimal state, thereby ensuring the stability and consistency of product quality and heat exchange efficiency.

[0084] The above embodiments can be implemented in whole or in part via software, hardware (e.g., circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. A computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions according to the embodiments of the present invention are fully or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired means (e.g., infrared, wireless, microwave, etc.). A computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0085] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0086] In this disclosure, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, "at least one of a, b, or c" can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural.

[0087] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0088] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0089] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0090] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0091] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0092] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0093] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or the portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0094] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. An intelligent temperature control system for a spiral flow channel high-efficiency heat dissipation injection mold, characterized in that: include: Melt data adaptation optimization module, holding pressure and temperature control adaptability optimization module, and thermal response quantification and judgment module; The melt data adaptation and optimization module is used to monitor the injection melt injected into the injection mold to reflect the melt injection data adaptation of the melt injection and temperature control conditions and perform melt data adaptation optimization to reduce the impact of injection changes of the injection melt on the melt temperature; The holding pressure and temperature control adaptability optimization module is used to determine the adjustment range of the holding pressure stage data and take corresponding holding pressure and temperature control adaptability optimization measures to reduce the impact of the holding pressure stage on the required temperature for injection molding; The thermal response quantification and determination module is used to quantify and determine the thermal response of the injection mold cavity within a cycle, and to perform cooling and heat dissipation temperature control adjustment according to the thermal response to ensure the heat dissipation effect of the injection mold cavity.

2. The intelligent temperature control system for a spiral flow channel high-efficiency heat dissipation injection mold according to claim 1, characterized in that: The monitoring of the injection melt injected into the injection mold to reflect the melt injection data adaptation of the melt injection and temperature control conditions and to perform melt data adaptation optimization is as follows: Acquiring injection melt data of a melt injected into an injection molding machine, wherein the injection melt data includes melt temperature and injection speed at an initial stage of injection molding; Comparing the injected melt data with the corresponding reference melt data interval and obtaining the corresponding melt reference interval median, wherein the reference melt data interval includes a melt temperature reference interval and an injection speed interval at the initial stage of injection molding, and the melt reference interval median includes a melt temperature median and an injection speed median; If the melt temperature is less than the minimum value of the melt temperature reference interval, the melt temperature is adjusted to the minimum value of the melt temperature reference interval; if the melt temperature is greater than the maximum value of the melt temperature reference interval, the melt temperature is adjusted to the maximum value of the melt temperature reference interval; If the injection speed at the initial stage of injection molding is less than the minimum value of the injection speed range at the initial stage of injection molding, the injection speed at the initial stage of injection molding is adjusted to the minimum value of the injection speed range at the initial stage of injection molding; if the injection speed at the initial stage of injection molding is greater than the maximum value of the injection speed range at the initial stage of injection molding, the injection speed at the initial stage of injection molding is adjusted to the maximum value of the injection speed range at the initial stage of injection molding; If the injection melt data all belong to the corresponding reference melt data interval, then obtain the proportion of each injection melt data in the corresponding reference melt data interval, and obtain the melt temperature proportion used to quantify the data distribution of the melt temperature in the melt temperature reference interval, and the injection speed proportion used to quantify the data distribution of the injection speed in the initial injection molding interval; The difference between the melt temperature ratio and the injection speed ratio is quantified to obtain the melt temperature-injection speed gap, which measures the adaptability difference between the melt temperature and the injection speed. If the melt temperature-injection speed difference is lower than the preset difference, no additional processing is performed. Otherwise, the corresponding melt temperature and injection speed at the beginning of injection molding are adjusted to the median melt temperature and injection speed.

3. The intelligent temperature control system for a spiral flow channel high-efficiency heat dissipation injection mold according to claim 1, characterized in that: The specific process of determining the adjustment range of the pressure holding stage data and taking corresponding pressure holding temperature control adaptability optimization measures is as follows: Adjust the injection speed at the initial stage of injection molding to the injection speed at the later stage of injection molding based on the injection molding standard, and obtain the corresponding holding pressure within the cycle, and obtain the change range of the injection speed and holding pressure at the later stage of injection molding within the cycle in real time; The adaptability of the injection speed variation range and the holding pressure variation range in the late stage of injection molding is quantified to obtain the holding pressure control adaptation amount that measures the balance between the variation range of the injection speed and the holding pressure in the late stage of injection molding. The holding pressure control adaptation amount is judged against the set adaptation amount error range and the corresponding maximum holding time limit is obtained based on the mold cavity temperature drop gradient mapping within the cycle period. If the holding pressure control adaptation amount falls within the adaptation amount error range, the corresponding holding time is obtained based on the holding pressure control adaptation amount mapping. If the holding time is lower than the maximum holding time limit, the injection molding melt is continued to be held based on the holding time; otherwise, the injection molding melt is continued to be held based on the maximum holding time limit. If the holding pressure control adaptation amount is less than the minimum value of the adaptation amount error interval, the injection speed reduction control rate influence amount and the holding pressure time influence amount are mapped based on the difference between the holding pressure control adaptation amount and the minimum value of the adaptation amount error interval. The corresponding injection speed reduction rate is controlled based on the injection speed reduction control rate influence amount. The optimized holding pressure time is obtained based on the holding pressure time influence amount and the initial holding pressure time. If the optimized holding pressure time is lower than the maximum limit of the holding pressure time, the injection molding melt is continued to be held based on the optimized holding pressure time. Otherwise, the injection molding melt is continued to be held based on the maximum limit of the holding pressure time. If the holding pressure control adaptation amount is greater than the maximum value of the adaptation amount error interval, the holding pressure rise control rate influence amount and the holding pressure time influence amount are obtained by mapping based on the difference between the holding pressure control adaptation amount and the maximum value of the adaptation amount error interval. The corresponding holding pressure rise speed is controlled based on the holding pressure rise control rate influence amount. The optimized holding pressure time is obtained by processing based on the holding pressure time influence amount and the initial holding pressure time. If the optimized holding pressure time is lower than the maximum limit of the holding pressure time, the injection molding melt is continued to be held based on the optimized holding pressure time. Otherwise, the injection molding melt is continued to be held based on the maximum limit of the holding pressure time.

4. The intelligent temperature control system for a spiral flow channel high-efficiency heat dissipation injection mold according to claim 1, characterized in that: The specific steps of quantifying and determining the thermal response of the mold cavity of the injection mold during the cycle are as follows: Step 1: Acquire thermal response data of the spiral flow channel using a detection device deployed in the injection mold to obtain a thermal response determination coefficient for quantifying the thermal response of the spiral flow channel. The thermal response data includes temperature adjustment time, temperature overshoot value, temperature callback time, temperature stabilization error, and thermal hysteresis time. The detection device includes a thermocouple, a temperature probe, and a flow sensor. Step 2: Compare the thermal response determination coefficient with the set thermal response determination range: If the thermal response determination coefficient falls within the set thermal response determination range, no additional processing is performed; If the thermal response determination coefficient is lower than the minimum value of the set thermal response determination range, the first thermal response optimization measure is executed to reduce the influence of slow thermal response on the cooling and heat dissipation of the injection molded product; If the thermal response determination coefficient is higher than the maximum value of the set thermal response determination range, the second thermal response optimization measure is executed to reduce the influence of the excessively fast thermal response on the cooling and heat dissipation of the injection molded product.

5. The intelligent temperature control system for a spiral flow channel high-efficiency heat dissipation injection mold according to claim 4, characterized in that: The specific method for obtaining the thermal response determination coefficient is as follows: Quantifying the temperature overshoot value and the overshoot maximum value proportionally to obtain a corresponding temperature overshoot index, wherein the proportional quantification is used to quantify the degree to which the temperature overshoot value deviates from the overshoot maximum value; After normalizing the temperature adjustment time, temperature callback time, temperature stabilization error, and thermal hysteresis time, logical fitting is performed to obtain the corresponding temperature adjustment time index, temperature callback time index, temperature stabilization error index, and thermal hysteresis time index respectively; Based on the temperature adjustment time index, temperature callback time index, temperature stability error index, thermal lag time index and temperature overshoot index, a thermal response determination coefficient is obtained after a weighted operation is performed with the corresponding thermal response analysis proportions. The thermal response analysis proportions include the temperature adjustment time analysis proportion, the temperature overshoot value analysis proportion, the temperature callback time analysis proportion, the temperature stability error analysis proportion and the thermal lag time analysis proportion.

6. The intelligent temperature control system for a spiral flow channel high-efficiency heat dissipation injection mold according to claim 4, characterized in that: The specific content of the first thermal response optimization measure is as follows: Obtaining the median value of the thermal response determination range and performing differential quantification on the difference between the median value and the thermal response determination coefficient to obtain a first ideal thermal response compensation value; and simultaneously performing differential quantification on the minimum value of the thermal response determination range and the thermal response determination coefficient to obtain a first minimum thermal response compensation value; Comparing the first minimum compensation value of the thermal response with the first ideal compensation value of the thermal response to obtain a first minimum compensation ratio of the thermal response; A first cooling water flow control ratio is obtained based on the projection of the first minimum compensation ratio of the thermal response, and the cooling water flow in the spiral flow channel is increased according to the first cooling water flow control ratio.

7. The intelligent temperature control system for a spiral flow channel high-efficiency heat dissipation injection mold according to claim 4, characterized in that: The specific content of the second thermal response optimization measure is as follows: Obtaining the median value of the thermal response determination range and quantifying the difference between the median value and the thermal response determination coefficient to obtain the second ideal thermal response compensation value; and simultaneously obtaining the difference between the maximum value of the thermal response determination range and the thermal response determination coefficient to obtain the second minimum thermal response compensation value; Comparing the second lowest thermal response compensation value with the second ideal thermal response compensation value to obtain a second minimum thermal response compensation ratio; A second control ratio of the cooling water flow is obtained based on the projection of the second minimum compensation ratio of the thermal response, and the cooling water flow in the spiral flow channel is reduced according to the second control ratio of the cooling water flow.

8. The intelligent temperature control system for a spiral flow channel high-efficiency heat dissipation injection mold according to claim 4, characterized in that: The thermal response determination coefficient is compared with the set thermal response determination range, and then the spiral flow channel improvement suggestions are output, as follows: If the first thermal response optimization measure is executed, a suggested increase in the number of spiral turns is obtained by querying the mapping table based on the first ideal thermal response compensation value, and the result is output to the operator terminal of the control system; If the second thermal response optimization measure is executed, the recommended reduction amount of the number of spiral turns is obtained by querying the mapping table based on the second ideal thermal response compensation value, and waits for output to the staff terminal of the control system.

9. The intelligent temperature control system for a spiral flow channel high-efficiency heat dissipation injection mold according to claim 1, characterized in that: The cooling and heat dissipation temperature control adjustment also includes the change trend adjustment, which is as follows: If the thermal response determination coefficient of the next cycle after temperature control adjustment is performed according to the thermal response situation falls within the thermal response determination range, no spiral flow channel improvement suggestions will be output and the waiting state will be maintained; If the thermal response determination coefficient is still lower than the minimum value of the set thermal response determination range, the cooling water flow rate of the next cycle is increased according to the increase in the cooling water flow rate based on the first cooling water flow control ratio until the thermal response determination coefficient falls within the set thermal response determination range. If the number of cycles reaches the cycle limit, the optimization cycle is stopped and the corresponding spiral flow channel improvement suggestions are sent to the control system staff terminal; If the thermal response determination coefficient is still higher than the maximum value of the set thermal response determination range, the cooling water flow of the next cycle is reduced according to the reduction amplitude of the cooling water flow based on the second control ratio of the cooling water flow until the thermal response determination coefficient falls within the set thermal response determination range. If the number of cycles reaches the cycle limit, the optimization cycle is stopped and the corresponding spiral flow channel improvement suggestions are sent to the staff terminal of the control system.

10. The intelligent temperature control system for a spiral flow channel high-efficiency heat dissipation injection mold according to claim 9, characterized in that: The change trend adjustment also includes: after each optimization cycle, obtaining the thermal response determination coefficient of the corresponding cycle, and quantifying the difference with the thermal response determination coefficient of the previous cycle to obtain the difference in cycle coefficients; if the difference in cycle coefficients is greater than the set difference, continuing the cycle processing; if the difference in cycle coefficients is not greater than the set difference, stopping the cycle and sending the corresponding spiral flow channel improvement suggestions to the staff terminal of the control system.

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