Injection molding parameter intelligent regulation system of injection molding machine

Abstract

This invention relates to the field of polymer material injection molding and automation control technology, specifically to an intelligent control system for injection molding machine parameters, comprising: a rheological digital twin and feedforward calculation unit: generating wavefront position prediction information based on key timestamps; a transient pulsation command generation unit: parsing the wavefront position prediction information and superimposing high-frequency micro-amplitude pulsation commands onto the macroscopic injection speed command; a high-frequency shear heat injection and physical phase change unit: reducing the local melt viscosity of the wavefront based on the high-frequency micro-amplitude pulsation commands; an energy decoupling and state recovery unit: monitoring the execution state of the high-frequency micro-amplitude pulsation commands, restoring the polymer melt to a high viscosity state and completing cooling and solidification; and an adaptive control and optimization unit: quantifying the microstructure filling rate of the microstructure region and optimizing the transient pulsation generation strategy according to the wavefront velocity fluctuation variance. This invention ensures the complete replication of the microstructure and robustness for long-term continuous production.

Description

Technical Field

[0001] This invention relates to the field of polymer material injection molding and automation control technology, specifically to an intelligent control system for injection molding machine injection parameters. Background Technology

[0002] Injection molding is the mainstream process for processing polymer materials. Its technical essence is to inject the melt into the mold cavity for cooling and solidification by controlling the mechanical mechanisms such as the screw and barrel of the injection molding machine. Injection molding machines usually use preset macroscopic injection speed commands for conventional smooth injection control. Existing injection process status monitoring and control mainly rely on physical devices such as mold cavity pressure sensors for closed-loop control. These traditional physical sensors can acquire state parameters in the macroscopic molding process and provide feedback guidance.

[0003] However, in the injection molding of microstructures such as precision medical microfluidic chips and ultra-thin shells for consumer electronics, there is often a problem of sudden changes in flow resistance caused by rapid changes in wall thickness in micron-level capillary channels; the closed-loop control of traditional cavity pressure sensors has an inherent irreversible hysteresis defect and cannot break through the delay limit of physical sensors; at the same time, the conventional method of increasing the overall macro temperature to reduce viscosity faces the technical bottleneck of mutually exclusive space filling rate and cooling curing efficiency.

[0004] Currently, for extreme injection molding scenarios involving minute and complex geometric features, it is necessary to accurately capture the interference of wavefront rheological states in advance and perform high-frequency transient intervention. Therefore, how to overcome the closed-loop hysteresis defect of traditional sensors and solve the problems of difficult filling of micro-structure areas and easy flow marks without increasing the cooling cycle has become a technical problem to be solved. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent control system for injection molding parameters of an injection molding machine, which solves the following technical problems: avoids material degradation and internal stress surge caused by wide-frequency oscillation, and effectively solves the problems of difficulty in filling micron-level capillary channels and easy generation of flow marks, thereby achieving transient control of wavefront viscosity without increasing the cooling cycle.

[0006] The objective of this invention can be achieved through the following technical solution: An intelligent injection parameter control system for an injection molding machine, applied to an injection molding machine including a screw and a barrel, wherein the injection molding machine has a preset macroscopic injection speed command, including: a rheological digital twin and feedforward calculation unit: acquiring the input three-dimensional geometric features of the mold, polymer physical property parameters, and initial injection process parameters, calculating the key timestamps of the wavefront of the polymer melt reaching the microstructure region within the mold cavity through a rheological digital twin model; generating wavefront position prediction information based on the key timestamps; a transient pulsation command generation unit: parsing the wavefront position prediction information, constructing a transient pulsation generation strategy based on Deborah number matching; converting the transient pulsation generation strategy into a high-frequency micro-amplitude pulsation command, and converting the high-frequency micro-amplitude pulsation command into a high-frequency micro-amplitude pulsation command. The pulsation command is superimposed on the macroscopic injection speed command; the high-frequency shear heat injection and physical phase change unit: based on the high-frequency micro-amplitude pulsation command, drives the screw to generate high-frequency micro-oscillations; the high-frequency micro-oscillations are propagated in the polymer melt and induce local shear heat generation on the wavefront, reducing the local melt viscosity on the wavefront; the energy decoupling and state recovery unit: monitors the execution state of the high-frequency micro-amplitude pulsation command; in response to the execution state being stopped, maintains the temperature of the barrel, so that the polymer melt returns to a high viscosity state and completes cooling and solidification; the adaptive control and optimization unit: quantifies the micro-structure filling rate of the micro-structure region, evaluates the wavefront velocity fluctuation variance; and optimizes the transient pulsation generation strategy based on the wavefront velocity fluctuation variance.

[0007] In one possible implementation, the method of obtaining the input three-dimensional geometric features of the mold, polymer property parameters, and initial injection process parameters, and calculating the key timestamp of the wavefront of the polymer melt reaching the microstructure region within the mold cavity using a rheological digital twin model includes: extracting spatial geometric parameters from the three-dimensional geometric features of the mold; inputting the spatial geometric parameters, the polymer property parameters, and the initial injection process parameters into the rheological digital twin model to simulate the flow process of the polymer melt within the mold cavity; tracking the wavefront position of the polymer melt and identifying the spatial interference state between the wavefront position and the microstructure region; and extracting the instantaneous time of the wavefront contacting the microstructure region as the key timestamp based on the spatial interference state, and integrating these to generate the wavefront position prediction information.

[0008] In one possible implementation, the method for identifying the spatial interference state between the wavefront position and the microstructure region includes: calculating the relative distance between the wavefront position and the microstructure region; if the relative distance is greater than a preset safety distance threshold, it is determined to be a non-interference state, and the conventional injection prediction is maintained; if the relative distance is less than or equal to the safety distance threshold and is greater than zero, it is determined to be a near-interference state, and the key timestamp extraction process is triggered; if the relative distance is less than or equal to zero, it is determined to be an interference state, the actual contact time is recorded, and the data is fed back to the rheological digital twin model for error correction.

[0009] In one possible implementation, the method of constructing a transient pulsation generation strategy based on Deborah number matching includes: obtaining the molecular chain relaxation time of the polymer melt; setting a target Deborah number based on the molecular chain relaxation time; calculating a target pulsation frequency according to the ratio of the target Deborah number to the molecular chain relaxation time, and setting a matching pulsation frequency range based on the target pulsation frequency, such that the pulsation frequency of the pulsation frequency range resonates with the molecular chain relaxation time; determining the pulsation amplitude in combination with the filling requirements of the microstructure region, and generating the transient pulsation generation strategy based on the pulsation frequency range and the pulsation amplitude.

[0010] In one possible implementation, the method of converting the transient pulsation generation strategy into a high-frequency micro-amplitude pulsation command and superimposing the high-frequency micro-amplitude pulsation command into the macroscopic injection speed command includes: extracting the pulsation frequency range and the pulsation amplitude from the transient pulsation generation strategy; generating a periodically changing basic displacement pulsation waveform based on the pulsation frequency range and the pulsation amplitude, and converting the basic displacement pulsation waveform into a basic velocity pulsation waveform by taking the time derivative of the basic displacement pulsation waveform; extracting the current macroscopic injection speed command of the system; and within a preset lead time window before the arrival of the key timestamp, using the basic velocity pulsation waveform as the high-frequency micro-amplitude pulsation command, superimposing it with the macroscopic injection speed command in the time domain to generate a composite injection drive command.

[0011] In one possible implementation, driving the screw to generate high-frequency micro-oscillations; propagating the high-frequency micro-oscillations in the polymer melt and inducing local shear heat generation on the wavefront includes: sending the composite injection drive command to the high-frequency servo drive module of the injection molding machine; the high-frequency servo drive module parsing the composite injection drive command and driving the screw to perform a linear propulsion action with high-frequency micro-amplitude pulsations to generate the high-frequency micro-oscillations; utilizing the acoustic conduction characteristics of the polymer melt, propagating the high-frequency micro-oscillations at the speed of sound towards the wavefront; when the high-frequency micro-oscillations reach the wavefront, intermolecular relative motion is induced through high-frequency friction, thereby inducing local shear heat generation on the wavefront.

[0012] In one possible implementation, reducing the local melt viscosity of the wavefront includes: monitoring the local shear heat accumulation of the wavefront; if the shear heat accumulation is lower than a preset thermal activation threshold, continuously injecting high-frequency oscillating energy; if the shear heat accumulation is greater than or equal to the thermal activation threshold, using the shear heat to break the entanglement state of the polymer molecular chains in the polymer melt; as the entanglement state of the polymer molecular chains is broken, a transient viscosity reduction effect of the wavefront is triggered, reducing the local melt viscosity of the wavefront to below a preset fillable rheological threshold.

[0013] In one possible implementation, the method of maintaining the temperature of the barrel in response to the execution state being stopped, so that the polymer melt can return to a high viscosity state and complete cooling and solidification, includes: monitoring the microstructure filling time window corresponding to the key timestamp; when the microstructure filling time window ends, switching the execution state to stop and canceling the high-frequency micro-amplitude pulsation command; shielding the heating compensation action of the barrel to maintain a constant temperature of the barrel; as the high-frequency micro-amplitude pulsation command is canceled, the shear heat disappears, the polymer molecular chains of the polymer melt reform entanglement, so that the polymer melt returns to a high viscosity state and completes cooling and solidification within the mold cavity.

[0014] In one possible implementation, quantifying the microstructure fill rate of the microstructure region and evaluating the wavefront velocity fluctuation variance; optimizing the transient pulsation generation strategy based on the wavefront velocity fluctuation variance includes: acquiring product image data after the injection molding cycle is completed, extracting the actual dimensions of the microstructure features in the microstructure region; using the ratio of the actual dimensions of the microstructure features to the theoretical dimensions of the mold's three-dimensional geometric features as the microstructure fill rate; extracting the wavefront movement trajectory recorded by the rheological digital twin model, and calculating the wavefront velocity fluctuation variance; if the wavefront velocity fluctuation variance is lower than a preset stability threshold, then marking the current transient pulsation generation strategy as the optimal strategy and saving it; if the wavefront velocity fluctuation variance is higher than or equal to the stability threshold, then dynamically adjusting the target Deborah number and the pulsation amplitude based on the deviation between the wavefront velocity fluctuation variance and the stability threshold, and updating the transient pulsation generation strategy.

[0015] The beneficial effects of this invention are:

[0016] 1) This invention calculates the key timestamps of wavefront arrival in the microstructure region using a rheological digital twin model and generates predictive information. This mechanism pre-locks the time target, eliminating the inherent irreversible hysteresis defect of traditional cavity pressure sensor closed-loop control. Through feedforward extrapolation in digital space, the system has the ability to predict physical boundaries, providing zero-delay feedforward basis for high-frequency intervention that exceeds the delay limit of physical sensors. 2) This invention superimposes high-frequency micro-amplitude pulsation commands onto macroscopic speed commands to drive screw oscillation, utilizing mechanical wave propagation to induce local shear heat generation on the wavefront to reduce viscosity. This method achieves long-distance targeted energy injection, instantly raising the local temperature through mechanical energy without affecting the overall macroscopic temperature of the barrel. This successfully overcomes the bottleneck of the mutual exclusion between space filling rate and cooling efficiency, solving the problem of difficult microchannel filling without increasing the cooling cycle.

[0017] 3) This invention monitors the execution status through an energy decoupling and state recovery unit, maintaining a constant barrel temperature to shield heating compensation when pulsation stops; viscosity reduction relies entirely on transient shear heat rather than macroscopic heating, achieving decoupling of system kinetic energy input and thermal energy retention; after pulsation is canceled, local shear heat dissipates rapidly, melt molecular chains re-entangle and quickly recover to a high viscosity state and freeze using the low temperature of the mold, preventing the product cooling cycle from being prolonged. 4) This invention adaptively quantifies the microstructure filling rate and evaluates the wavefront velocity fluctuation variance, dynamically adjusting the target matching point to optimize the transient pulsation generation strategy; this closed-loop iterative optimization mechanism based on the final quality of the product endows the system with the ability to automatically find optimal parameters when facing batch-to-batch material fluctuations or environmental temperature drift interference; this mechanism effectively measures the determinism of rheological control, ensuring the complete replication of microstructures and robustness for long-term continuous production. Attached Figure Description

[0018] The invention will now be further described with reference to the accompanying drawings.

[0019] Figure 1 This is a schematic diagram of a module of an intelligent control system for injection parameters of an injection molding machine provided in an embodiment of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Please see Figure 1An intelligent injection parameter control system for injection molding machines is applied to injection molding machines that include screws and barrels. The injection molding machine has preset macroscopic injection speed commands. In the injection molding scenario of precision medical microfluidic chips, it solves the problem of difficult filling of micron-level capillary channels and easy generation of flow marks.

[0022] The rheological digital twin and feedforward calculation unit in the system acquires the input three-dimensional geometric features of the mold, polymer physical property parameters, and initial injection process parameters. It calculates the key timestamps of the wavefront of the polymer melt reaching the micro-structure region in the mold cavity through the rheological digital twin model. The key timestamps are defined in the specific technical environment of this invention as the precise millisecond-level moments when the melt flow front is about to spatially interfere with the complex micro-geometric features in the mold cavity. They represent a high-precision time coordinate reference with feedforward characteristics.

[0023] Wavefront position prediction information is generated based on key timestamps. This parameter is set to ensure that zero-delay feedforward is provided for subsequent high-frequency interventions. This indicator signifies that the system has the ability to predict physical boundaries. The transient pulsation command generation unit analyzes the wavefront position prediction information and constructs a transient pulsation generation strategy based on Deborah number matching.

[0024] The transient pulsation generation strategy represents the control logic that actively introduces mechanical oscillations within a specific extremely short time window. It aims to break the inherent process mode of conventional smooth injection, transform the transient pulsation generation strategy into a high-frequency micro-amplitude pulsation command, and superimpose the high-frequency micro-amplitude pulsation command into the macro injection speed command. During this period, the high-frequency shear heat injection and physical phase change unit are based on the high-frequency micro-amplitude pulsation command.

[0025] Specifically, it is based on a composite injection drive command generated by the time-domain superposition of high-frequency micro-amplitude pulsation command and macro injection speed command, which drives the screw to generate high-frequency micro-oscillation, propagates the high-frequency micro-oscillation in the polymer melt and induces local shear heat on the wavefront.

[0026] In this scheme, shear heat specifically refers to the internal energy dissipated between fluid layers due to high-frequency relative friction. Its unique technical consideration is to instantly increase the local temperature through mechanical energy conversion without affecting the overall macroscopic temperature. This shear heat is used to reduce the local melt viscosity on the wavefront. After filling is completed, the energy decoupling and state recovery unit monitors the execution status of the high-frequency micro-amplitude pulsation command.

[0027] In response to the execution state being stopped, the temperature of the barrel is maintained to restore the polymer melt to a high viscosity state and complete cooling and solidification. At the same time, the microstructure filling rate of the unit quantification microstructure region is adaptively controlled and optimized. The wavefront velocity fluctuation variance is evaluated in combination with the microstructure filling rate, and the transient pulsation generation strategy is optimized based on the wavefront velocity fluctuation variance.

[0028] This embodiment demonstrates the process adaptability in the formation of complex microchannels. By introducing a cascade mechanism of feedforward calculation and high-frequency micro-pulsation superposition, and utilizing the low delay characteristics of mechanical waves propagating in fluids, transient control of wavefront viscosity is achieved without increasing the cooling cycle. This verifies the robustness of this technical solution under transient control of micro-rheological states.

[0029] In a preferred embodiment of the present invention, the method of acquiring the input three-dimensional geometric features of the mold, polymer physical property parameters, and initial injection process parameters, and calculating the key timestamps of the wavefront of the polymer melt reaching the microstructure region within the mold cavity through a rheological digital twin model is specified. In the production scenario of ultra-thin shells for consumer electronics, in response to the problem of abrupt changes in flow resistance caused by rapid changes in wall thickness, the rheological digital twin and feedforward solution unit extract the spatial geometric parameters of the three-dimensional geometric features of the mold, namely the three-dimensional topological data such as the depth, width, and curvature of the microchannel.

[0030] Spatial geometric parameters, polymer properties, and initial injection molding process parameters are input into a rheological digital twin model to simulate the flow process of polymer melt within the mold cavity. This simulation step is designed to ensure that the feedforward extrapolation of the entire physical field is completed in a purely digital space. Specifically, the finite element analysis method is used to discretize and solve the three-dimensional flow field. During the simulation, the wavefront position of the polymer melt is continuously tracked, and the spatial interference state between the wavefront position and the microstructure region is identified. This index indicates the dynamic topological relationship between the melt front and the physical mold boundary.

[0031] Based on the spatial interference state, the instantaneous time of the wavefront contact with the microstructure region is extracted as the key timestamp and integrated to generate wavefront position prediction information.

[0032] This embodiment demonstrates the application of digital twin technology in predicting the rheological limits of injection molding. By locking the millisecond-level time target point in advance, it eliminates the inherent irreversible hysteresis defect of traditional cavity pressure sensor closed-loop control, and verifies the high temporal resolution and robustness of this solution in predicting the filling of complex geometries.

[0033] In a preferred embodiment of the present invention, the method for identifying the spatial interference state between the wavefront position and the microstructure region is as follows: in the optical lens microprism array forming scenario, in order to accurately capture the optimal time interval for high-frequency pulsation triggering, the rheological digital twin and feedforward solution unit calculates the relative distance between the wavefront position and the microstructure region in real time. This relative distance is calculated by introducing a distance evaluation model.

[0034] The data input required by the model comes from the discretized spatial grid node coordinates output by the rheological digital twin model at the current inference time step, specifically by calculating the wavefront point set composed of the current wavefront grid node coordinates. wavefront nodes in The set of structural points composed of the coordinates of the nodes of the microstructured surface mesh Boundary nodes in Euclidean distance or L2 norm between The minimum value is used to obtain the relative distance. The calculation formula is as follows: ; where subscript Represents the wavefront point set, subscript Representing a microstructure point set, by calculating the elements between two point sets. The minimum norm value determines the relative distance.

[0035] The model is set to ensure the establishment of a scientific response echelon. The logic for setting the preset safety distance threshold is as follows: it is determined by the sum of the minimum feature size of the grid division in the rheological digital twin model and the maximum flow step size of the polymer melt in one control cycle, to ensure that the system has sufficient response time before interference occurs. It is usually set in the range of 0.5 mm to 2.0 mm.

[0036] Based on the above distance calculation, if the relative distance is greater than the preset safe distance threshold, it is determined to be in a non-interference state and the normal injection prediction is maintained. If the relative distance is less than or equal to the safe distance threshold and greater than zero, it is determined to be in a near-interference state. At this time, the system triggers the key timestamp extraction process. This state marks that the system has entered a high-alert stage of dynamic mismatch. If the relative distance is less than or equal to zero, it is determined to be in an interference state. At this time, the actual contact time is recorded and fed back to the rheological digital twin model for error correction.

[0037] This embodiment demonstrates the process adaptability of a three-level dynamic interference determination mechanism based on spatial distance. This mechanism prevents energy dissipation caused by premature triggering and avoids melt front freezing caused by late triggering, verifying the robustness of this technical solution in micro-nano structure interface tracking.

[0038] In a preferred embodiment of the present invention, a transient pulsation generation strategy based on Deborah number matching is constructed. In the injection molding scenario of thin-walled parts for high-frequency communication connectors, in order to generate a synergistic deentanglement effect between external mechanical disturbances and the internal motion of polymer chains, the transient pulsation command generation unit obtains the molecular chain relaxation time of the polymer melt and sets the target Deborah number based on the molecular chain relaxation time.

[0039] In this step, the target Deborah number is set based on the critical untangling experimental benchmark value of a specific polymer during shear thinning, typically within a range greater than or equal to 1 and less than or equal to 10 to ensure the induction of nonlinear rheological effects. This is achieved by introducing a dynamic resonance matching mechanism, specifically by setting the target Deborah number... Divide by molecular chain relaxation time The target pulsation frequency was calculated. Its formula is: .

[0040] The matching mechanism is set to ensure that the injected mechanical pulsation frequency resonates with the intrinsic relaxation time of the polymer molecular chain. After calculating the target pulsation frequency based on the ratio of the target Deborah number to the molecular chain relaxation time, a matching pulsation frequency range is set based on the target pulsation frequency so that the pulsation frequency of the pulsation frequency range resonates with the molecular chain relaxation time. Finally, the pulsation amplitude is determined in combination with the filling requirements of the microstructure region.

[0041] Specifically, the minimum feature size of the microchannel width is extracted. As a benchmark, a pre-defined empirical coefficient related to the polymer modulus is introduced. The pulsation amplitude is calculated using an inverse proportional mapping relationship. Its calculation logic is as follows: .

[0042] To ensure dimensional consistency, empirical coefficients are preset. Having the dimension of area, such as square millimeters, its physical meaning is the critical area constant required for a specific polymer to maintain effective molecular chain detangling under a reference shear stress. It is obtained through prior rheometer calibration, and a hard limiting operator is introduced. If the calculated... If the amplitude is less than 5% or greater than 15% of the microchannel feature size, it is forcibly clamped to the corresponding boundary value of that range to ensure that the amplitude is between 5% and 15% of the microchannel feature size, thereby avoiding excessive mechanical deformation that would cause excessive internal stress in the product or insufficient amplitude to induce shear heat.

[0043] Based on the transient pulsation generation strategy using pulsation frequency range and pulsation amplitude, this embodiment demonstrates a rheological constitutive control method based on polymer physical properties. By inducing a strong molecular chain de-entanglement effect through a small mechanical amplitude, a significant viscosity reduction effect is achieved with low mechanical energy consumption. This effectively avoids material degradation and internal stress surge caused by broadband oscillations, verifying the robustness of this technical solution in the control of complex polymer physical phase transitions.

[0044] In a preferred embodiment of the present invention, the specific method of converting the transient pulsation generation strategy into a high-frequency micro-amplitude pulsation command and superimposing the high-frequency micro-amplitude pulsation command into the macro injection speed command is, in the scenario of injection molding of ultra-thin smartphone shells, to implant high-frequency disturbances without interfering with the macro filling rhythm.

[0045] The transient pulsation command generation unit extracts the pulsation frequency range and pulsation amplitude from the transient pulsation generation strategy, generates a periodically changing basic displacement pulsation waveform based on the pulsation frequency range and pulsation amplitude, i.e., a sine wave or a triangular wave, and calculates the time derivative of the basic displacement pulsation waveform to convert it into a basic velocity pulsation waveform.

[0046] Extract the current macroscopic injection speed command of the system, and within a preset lead time window before the arrival of the key timestamp, use the basic speed pulsation waveform as a high-frequency micro-amplitude pulsation command and superimpose it with the macroscopic injection speed command in the time domain to generate a composite injection drive command. Set this time domain superposition step to ensure that the mechanical actuator can simultaneously perform the dual tasks of macroscopic propulsion and microscopic oscillation. This indicator marks the deep integration state of multi-scale control commands.

[0047] This embodiment demonstrates an instruction cascading mechanism in a highly dynamic injection molding process. By seamlessly integrating high-frequency disturbances into the conventional injection speed curve, it achieves a coordinated response between macroscopic stable propulsion and microscopic transient intervention, verifying the robustness of this technical solution in complex electromechanical coupling systems.

[0048] In a preferred embodiment of the present invention, the method of driving the screw to generate high-frequency micro-oscillations and propagating the high-frequency micro-oscillations in the polymer melt and inducing local shear heat generation on the wavefront is used to address the physical phenomenon of a sharp increase in filling resistance in the small area of ​​the tooth root in the micro-precision gear injection molding scenario.

[0049] The high-frequency shear hot injection and physical phase change unit sends the composite injection drive command to the high-frequency servo drive module of the injection molding machine. The high-frequency servo drive module analyzes the composite injection drive command and drives the screw to perform a linear propulsion action with high-frequency micro-amplitude pulsation, thereby generating high-frequency micro-oscillation.

[0050] The acoustic conduction characteristics of polymer melt are used to propagate high-frequency micro-oscillations at the speed of sound towards the wavefront. This acoustic conduction path is set to ensure the elimination of the response lag problems of traditional mechanical valve action delay and extremely slow heat conduction temperature regulation. When the high-frequency micro-oscillations reach the wavefront, the velocity gradient is intensified due to the sudden change in the cross-sectional area of ​​the flow channel in the wavefront region. This induces strong relative motion between molecules through high-frequency friction, thereby generating local shear heat on the wavefront.

[0051] This embodiment demonstrates the non-obviousness of mechanical energy targeted to a wavefront, and realizes long-distance targeted energy injection by utilizing the high-speed propagation characteristics of mechanical waves in non-Newtonian fluids, verifying the robustness of this technical solution in cross-scale energy transfer processes.

[0052] In a preferred embodiment of the present invention, the method of reducing the local melt viscosity of the wavefront is used in the injection molding scenario of replicating the micro-nano structure of the light guide plate. In order to accurately control the physical boundary of energy injection and avoid material thermal degradation, the high-frequency shear heat injection and physical phase change unit monitor the local shear heat accumulation of the wavefront in real time. This accumulation is calculated by the thermal activation evolution model. The flow field physical quantities required by the model are all calculated in real time by the rheological digital twin model in each control cycle and mapped to the current wavefront physical space.

[0053] Specifically, the start time triggered by the high-frequency micro-amplitude pulsation command. up to the current time For time integration variables The integration interval for the transient viscosity output by the rheological digital twin model. With time-varying shear rate function Integrate the product of the squares of the products.

[0054] Transient viscosity It concerns the shear rate function and the time-varying temperature function output by the rheological digital twin model. The function is obtained by multiplying the integral result by the effective volume of the local high-frequency oscillations of the wavefront. The effective volume of high-frequency oscillation The numerical value is obtained by extracting the sum of the volumes of fluid mesh elements located in the critical interference region of the wavefront and affected by high-frequency oscillations in the rheological digital twin model, thereby calculating the cumulative shear heat with the physical dimension of energy Joules. Its formula is: ; where subscript Represents cut, subscript It is valid. As the time integral variable, this formula achieves quantitative calculation of heat by integrating the energy dissipation within the local effective volume of the wavefront in the time domain; wherein, the time step of integration must be set to be less than or equal to one-tenth of the high-frequency micro-amplitude pulsation command cycle to ensure the sampling accuracy of energy accumulation calculation.

[0055] The thermodynamic integral model is set to ensure accurate quantification of energy dissipation within a specific time window. Based on this accumulated amount, if the accumulated shear heat is lower than the preset thermal activation threshold, high-frequency oscillating energy injection continues. If the accumulated shear heat is greater than or equal to the thermal activation threshold, the entanglement state of the polymer molecular chains in the polymer melt is broken instantaneously using shear heat. The setting logic of the thermal activation threshold is as follows: it is calculated based on the difference between the target polymer's de-entanglement critical temperature (i.e., the target viscosity reduction temperature at which the polymer molecular chains transition from a highly entangled state to a fully relaxed state) and the current melt temperature, combined with the specific heat capacity and the critical latent heat of phase change required for de-entanglement. This aims to ensure that the accumulated internal energy is sufficient to overcome the secondary bond forces between molecular chains. As the entanglement state of the polymer molecular chains is broken, a transient viscosity reduction effect is triggered on the wavefront, causing the local melt viscosity on the wavefront to decrease nonlinearly and rapidly to below the preset fillable rheological threshold.

[0056] The fillable rheological threshold is the upper limit of critical viscosity derived from the microstructure size in the mold cavity and the maximum allowable injection pressure. It is used to ensure that the melt can fill smoothly without causing micro-flow marks. This index indicates that the polymer melt has completed the physical phase transition from a high viscosity state to a low viscosity state in a local space. This embodiment demonstrates the process adaptability of viscosity control only in the local space of the wavefront under the constraint of no increase in macroscopic barrel temperature. It breaks through the technical bottleneck of mutual exclusion between space filling rate and cooling solidification efficiency, and verifies the robustness of this technical solution in micro-thermodynamic state control.

[0057] In a preferred embodiment of the present invention, in response to the execution state of stopping the maintenance of the barrel temperature to restore the polymer melt to a high viscosity state and complete cooling and solidification, in the injection molding scenario of porous filter cartridges, this is to prevent the extended product cooling cycle from affecting the overall production cycle.

[0058] The energy decoupling and state recovery unit continuously monitors the microstructure filling time window corresponding to the key timestamp. When the microstructure filling time window ends, that is, the moment the microstructure is just filled, the execution state is quickly switched to stop and cancel the high-frequency micro-amplitude pulsation command. At the same time, the heating compensation action of the barrel is forcibly shielded to keep the barrel temperature constant, that is, no additional external heat source is provided. This forced shielding step is set to ensure the decoupling of the system's kinetic energy input and thermal energy residence. As the high-frequency micro-amplitude pulsation command is canceled, the local shear heat is quickly dissipated to the surrounding cooler mold steel and disappears. After losing the high-frequency excitation force, the polymer molecular chains of the polymer melt re-form entanglement, so that the polymer melt instantly returns to a high viscosity state and quickly completes cooling and solidification in the mold cavity.

[0059] This embodiment demonstrates an innovative design in which the viscosity reduction process relies entirely on transient shear heat rather than macroscopic heating, enabling the melt to be rapidly frozen using the low temperature of the mold. This improves the quality of microstructure forming while maintaining a short cooling cycle, verifying the robustness of this technical solution in controlling thermal hysteresis and resetting the state.

[0060] In a preferred embodiment of the present invention, the specific method of evaluating the wavefront velocity fluctuation variance based on the microstructure filling rate of the microstructure region and optimizing the transient pulsation generation strategy based on the wavefront velocity fluctuation variance is used to establish a closed-loop iterative optimization mechanism based on the final quality of the product in the automotive precision connector injection molding scenario facing batch-to-batch material fluctuations.

[0061] After the injection molding cycle is completed, the adaptive control and optimization unit collects product image data and scans the microchannel replica morphology with a high-resolution industrial camera to extract the actual one-dimensional feature length of the microstructure features in the microstructure region. The ratio of the actual one-dimensional feature length of the microstructure features to the theoretical one-dimensional feature length of the mold's three-dimensional geometric features is used as the microstructure filling rate. The wavefront movement trajectory recorded by the rheological digital twin model is extracted.

[0062] The movement trajectory consists of a sequence of multiple discrete-time sampling points within a time window filled with fine structures. To prevent program crashes caused by division by zero, a very small positive number is introduced. The fill rate of the fine structure is smoothed, and the smoothed fill rate is introduced as a penalty weight to calculate the variance of wavefront velocity fluctuation. This penalty weight increases the variance of the unfilled area, thereby guiding the algorithm to prioritize the optimization of weak parts with lower fill rates.

[0063] In the specific calculation, the total number of sampling points in the discrete-time sampling point sequence is used. Get the index of the current sampling point The corresponding number Instantaneous velocity of the wavefront advancing in the normal direction at each time sampling point Calculate the arithmetic mean of the instantaneous velocities at all sampling points. The underlined value represents the statistical average, which is calculated using the following formula: .

[0064] The velocity variance term is obtained; at the same time, a value that is usually taken as... The smallest positive number With microstructure filling rate The sum of these values ​​is used as the smoothing denominator to calculate the weighted wavefront velocity fluctuation index, which characterizes the variance of wavefront velocity fluctuations. Its formula is: .

[0065] The evaluation mechanism is set up to ensure the determinism of microrheological control. If the variance of wavefront velocity fluctuation is lower than the preset stability threshold, where the stability threshold is the maximum allowable velocity fluctuation variance extreme value that can ensure the complete replication of micro-nano structures, which is calculated based on historical good product production data, the current transient pulsation generation strategy is marked as the optimal strategy and saved as the standard template for subsequent batches.

[0066] If the variance of the wavefront velocity fluctuation is higher than or equal to the stability threshold, the target Deborah number and the pulsation amplitude are dynamically adjusted using the gradient descent algorithm based on the deviation between the variance of the wavefront velocity fluctuation and the stability threshold. This update the transient pulsation generation strategy for the execution of the next injection cycle.

[0067] The specific adjustment logic of the gradient descent algorithm is as follows: The weighted wavefront velocity fluctuation index is adjusted... The square of the deviation from the stability threshold is used as the loss function. Since the analytical partial derivative of this loss function cannot be directly obtained in the actual injection molding process, the system adopts the finite difference small perturbation method. In adjacent injection cycles, positive and negative small incremental perturbations are applied to the target Deborah number and the pulsation amplitude, respectively, and the corresponding changes in the variance of the wavefront velocity fluctuation are recorded. The partial derivatives of the loss function with respect to the target Deborah number and the pulsation amplitude, i.e., the gradient, are approximated by the difference ratio.

[0068] The adjustment direction is determined by the sign of the partial derivatives, and the adjustment step size is obtained by multiplying the absolute values ​​of the partial derivatives of the target Deborah number and the pulsation amplitude by the corresponding preset learning rate in the opposite direction of the gradient. The first learning rate is dimensionless for the target Deborah number, and the second learning rate with the dimension of length is used for the pulsation amplitude. This guides the fluctuation variance to converge to below the stable threshold within a finite iteration period. This embodiment demonstrates the process adaptability of constructing a deep closed loop by using the microscopic wavefront velocity fluctuation variance as the core indicator. It gives the system the ability to automatically find the optimal Deborah number matching point under environmental temperature drift interference and verifies the robustness of this technical solution in long-term continuous production.

[0069] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. An intelligent control system for injection molding parameters of an injection molding machine, applied to an injection molding machine including a screw and a barrel, wherein the injection molding machine has a preset macroscopic injection speed command, characterized in that, include: Rheological digital twin and feedforward calculation unit: acquires the input three-dimensional geometric features of the mold, polymer physical property parameters and initial injection process parameters, and calculates the key timestamps of the wavefront of the polymer melt reaching the microstructure region in the mold cavity through the rheological digital twin model; Wavefront position prediction information is generated based on the key timestamps; Transient pulse command generation unit: parses the wavefront position prediction information and constructs a transient pulse generation strategy based on Deborah number matching; The transient pulsation generation strategy is converted into a high-frequency micro-amplitude pulsation command, and the high-frequency micro-amplitude pulsation command is superimposed on the macroscopic injection speed command; High-frequency shear heat injection and physical phase change unit: Based on the high-frequency micro-amplitude pulsation command, the screw is driven to generate high-frequency micro-oscillation; the high-frequency micro-oscillation is propagated in the polymer melt and induces local shear heat generation on the wavefront, thereby reducing the local melt viscosity on the wavefront; Energy decoupling and state recovery unit: monitors the execution state of the high-frequency micro-amplitude pulsation command; in response to the execution state being stopped, maintains the temperature of the barrel, so that the polymer melt returns to a high viscosity state and completes cooling and solidification; Adaptive control and optimization unit: quantifies the microstructure filling rate of the microstructure region, evaluates the wavefront velocity fluctuation variance, and optimizes the transient pulsation generation strategy based on the wavefront velocity fluctuation variance.

2. The intelligent control system for injection molding parameters of an injection molding machine according to claim 1, characterized in that, The method of obtaining the input mold three-dimensional geometric features, polymer physical property parameters and initial injection process parameters, and calculating the key timestamps of the wavefront of the polymer melt reaching the microstructure region in the mold cavity through a rheological digital twin model includes: extracting the spatial geometric parameters of the three-dimensional geometric features of the mold; The spatial geometry parameters, polymer properties, and initial injection process parameters are input into the rheological digital twin model to simulate the flow process of the polymer melt within the mold cavity. Track the wavefront position of the polymer melt and identify the spatial interference state between the wavefront position and the microstructure region; Based on the spatial interference state, the instantaneous time of the wavefront contact with the microstructure region is extracted as the key timestamp, and integrated to generate the wavefront position prediction information.

3. The intelligent control system for injection molding parameters of an injection molding machine according to claim 2, characterized in that, The method for identifying the spatial interference state between the wavefront position and the microstructure region includes: calculating the relative distance between the wavefront position and the microstructure region; If the relative distance is greater than the preset safe distance threshold, it is determined to be a non-interference state and the normal injection prediction is maintained; if the relative distance is less than or equal to the safe distance threshold and is greater than zero, it is determined to be a near-interference state and the key timestamp extraction process is triggered. If the relative distance is less than or equal to zero, it is determined to be an interference state, the actual contact time is recorded and fed back to the rheological digital twin model for error correction.

4. The intelligent control system for injection molding parameters of an injection molding machine according to claim 1, characterized in that, The method for constructing a transient pulsation generation strategy based on Deborah number matching includes: obtaining the molecular chain relaxation time of the polymer melt; and setting a target Deborah number based on the molecular chain relaxation time. The target pulsation frequency is calculated based on the ratio of the target Deborah number to the molecular chain relaxation time, and a matching pulsation frequency range is set based on the target pulsation frequency, so that the pulsation frequency of the pulsation frequency range resonates with the molecular chain relaxation time. Based on the filling requirements of the microstructure region, the pulsation amplitude is determined, and the transient pulsation generation strategy is generated based on the pulsation frequency range and the pulsation amplitude.

5. The intelligent control system for injection molding parameters of an injection molding machine according to claim 4, characterized in that, The method of converting the transient pulsation generation strategy into a high-frequency micro-amplitude pulsation command and superimposing the high-frequency micro-amplitude pulsation command into the macroscopic injection speed command includes: extracting the pulsation frequency range and the pulsation amplitude from the transient pulsation generation strategy; Based on the pulsation frequency range and the pulsation amplitude, a periodically changing basic displacement pulsation waveform is generated, and the time derivative of the basic displacement pulsation waveform is calculated to convert it into a basic velocity pulsation waveform; the current macroscopic injection speed command of the system is extracted. Within a preset lead time window before the arrival of the critical timestamp, the basic velocity pulsation waveform is used as the high-frequency micro-amplitude pulsation command and superimposed with the macro injection speed command in the time domain to generate a composite injection drive command.

6. The intelligent control system for injection molding parameters of an injection molding machine according to claim 5, characterized in that, The drive screw generates high-frequency micro-oscillations; The method of propagating the high-frequency micro-oscillation in the polymer melt and inducing local shear heat generation on the wavefront includes: sending the composite injection drive command to the high-frequency servo drive module of the injection molding machine; The high-frequency servo drive module parses the composite injection drive command and drives the screw to perform a linear propulsion action with high-frequency micro-amplitude pulsation, generating the high-frequency micro-oscillation; Utilizing the acoustic conduction properties of the polymer melt, the high-frequency micro-oscillation propagates at the speed of sound toward the wavefront; when the high-frequency micro-oscillation reaches the wavefront, relative motion between molecules is induced by high-frequency friction, thereby inducing local shear heat generation on the wavefront.

7. The intelligent control system for injection molding parameters of an injection molding machine according to claim 6, characterized in that, The method of reducing the local melt viscosity of the wavefront includes: monitoring the local shear heat accumulation of the wavefront; If the accumulated shear heat is lower than the preset thermal activation threshold, high-frequency oscillation energy injection will continue. If the accumulated shear heat is greater than or equal to the thermal activation threshold, the shear heat is used to break the entanglement of the polymer molecular chains in the polymer melt. As the entanglement of the polymer molecular chains is broken, the transient viscosity reduction effect of the wavefront is triggered, causing the local melt viscosity of the wavefront to decrease to below a preset fillable rheological threshold.

8. The intelligent control system for injection molding parameters of an injection molding machine according to claim 1, characterized in that, The method of maintaining the temperature of the barrel in response to the execution state being stopped, so that the polymer melt can be restored to a high viscosity state and complete cooling and solidification, includes: monitoring the microstructure filling time window corresponding to the key timestamp; When the filling time window of the microstructure ends, the execution state is switched to stop, and the high-frequency micro-amplitude pulsation command is revoked; The heating compensation action of the barrel is shielded to maintain a constant temperature of the barrel; as the high-frequency micro-amplitude pulsation command is withdrawn, the shear heat disappears, the polymer molecular chains of the polymer melt reform entanglement, the polymer melt returns to a high viscosity state, and cooling and solidification are completed in the mold cavity.

9. The intelligent control system for injection molding parameters of an injection molding machine according to claim 4, characterized in that, The method of quantifying the microstructure filling rate of the microstructure region and evaluating the wavefront velocity fluctuation variance; and optimizing the transient pulsation generation strategy based on the wavefront velocity fluctuation variance includes: acquiring product image data after the injection molding cycle is completed and extracting the actual size of the microstructure features of the microstructure region. The ratio of the actual size of the microstructure feature to the theoretical size of the three-dimensional geometric feature of the mold is used as the microstructure filling rate; the wavefront movement trajectory recorded by the rheological digital twin model is extracted, and the wavefront velocity fluctuation variance is calculated; If the variance of the wavefront velocity fluctuation is lower than the preset stability threshold, the current transient pulsation generation strategy is marked as the optimal strategy and saved. If the variance of the wavefront velocity fluctuation is higher than or equal to the stability threshold, the target Deborah number and the pulsation amplitude are dynamically adjusted according to the deviation between the variance of the wavefront velocity fluctuation and the stability threshold, and the transient pulsation generation strategy is updated.

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