Intelligent management and control system for whole injection molding process of automotive trim panel

Abstract

The invention relates to the technical field of plastic injection molding, and discloses an intelligent management and control system for the whole injection molding process of an automotive trim panel, and the system comprises an entropy sensing unit which directly converts the physical pressure pulsation at a nozzle into a simulated entropy voltage signal; the distributed self-balancing execution unit is used for adaptively adjusting process parameters according to the signal and the injection molding initial pressure change rate; the physical collaboration and health diagnosis unit utilizes the same current loop to achieve inter-unit compensation and evaluate the health state of the actuator online, and by establishing direct physical perception on the flow state of the melt, the dependence of a traditional control mode on preset parameters is avoided; and then through analysis of sensing information in different dimensions, automatic adaptation to material changes and online diagnosis of physical health of the system are achieved, and the operation reliability of the injection molding process is improved.

Description

Technical Field

[0001] The present invention relates to an intelligent control system for the entire injection molding process of an automobile interior trim panel, and belongs to the technical field of plastic injection molding. Background Art

[0002] Currently, in the injection molding of products such as automotive interior panels, the common technical approach is to set a set of process parameters through a control system and maintain this set of process parameters constant during the production cycle. This control method is set based on ideal production conditions, but the actual flow process of the polymer melt in the mold cavity and the production boundary conditions themselves are dynamically changing.

[0003] On the one hand, when the batches of raw materials used in production change, their physical properties such as melt index and viscosity will also change accordingly. Continuing to use the original process parameter combination will affect the molding quality. On the other hand, after long-term operation, the mechanical properties of actuators such as hydraulic valves in the control system will be degraded, resulting in a deviation between their actual response to control instructions and the expected response, and the control system lacks a way to monitor this deviation.

[0004] Specifically, the existing technologies have the following major deficiencies: 1. The control system lacks the ability to physically perceive the actual flow state of the melt within the mold cavity in real time, resulting in a delayed response to molding defects caused by flow instability; 2. The control system is unable to identify subtle changes in the physical properties of raw materials online or perceive the decline in the health of key actuators, making it difficult to achieve adaptive adjustment and proactive maintenance of dynamic production boundary conditions. Therefore, how to construct an injection molding control system that can not only monitor the core flow state of the melt in real time, but also simultaneously identify material properties and assess the health of its own actuators online, thereby achieving closed-loop control from passive parameter execution to multi-dimensional state self-perception, has become the technical problem to be solved by this invention. Summary of the Invention

[0005] The present invention provides an intelligent control system for the entire injection molding process of automotive interior panels. Its main purpose is to solve the problem that existing injection molding control systems are unable to perceive the melt flow state in real time, adapt to material changes, and diagnose the health of actuators online, resulting in limited control accuracy and operational reliability.

[0006] To achieve the above objectives, the present invention provides an intelligent control system for the entire process of automobile interior panel injection molding, comprising:

[0007] an entropy sensing unit, the entropy sensing unit comprising a differential pressure sensor disposed at a nozzle of an injection molding unit and a hardware filtering and amplifying circuit connected to the differential pressure sensor, the hardware filtering and amplifying circuit being configured to output, based on a pressure signal sensed by the differential pressure sensor, an analog entropy voltage signal whose amplitude is modulated by the intensity of microscopic pressure pulsations in the pressure signal;

[0008] A distributed self-balancing execution unit, configured to receive an analog entropy voltage signal, includes a hardware differential circuit configured to generate a signal representing the injection pressure change rate during the initial phase of the injection molding cycle, and a threshold dynamic calibration module configured to determine a voltage threshold suitable for the current injection molding material from a plurality of reference voltages based on the injection pressure change rate signal. The distributed self-balancing execution unit also includes a three-state determination circuit configured to compare the analog entropy voltage signal with a voltage threshold and output a switching signal accordingly. The switching signal is used to control the injection rate and holding pressure parameters of the unit.

[0009] A physical collaboration and health diagnosis unit, which includes a 4mA to 20mA current loop for transmitting signals between multiple injection molding units and a hardware bandpass filter connected in series with the 4mA to 20mA current loop. The hardware bandpass filter has a passband in a predetermined frequency range and is configured to extract a current ripple signal within the predetermined frequency range from the loop current of the 4mA to 20mA current loop.

[0010] Preferably, the threshold dynamic calibration module includes a voltage comparator, which is configured to compare the signal representing the injection pressure change rate generated by the hardware differential circuit with multiple reference voltages representing the standard pressure slopes of different reference materials, and output a selection signal to the three-state determination circuit based on the comparison result to determine one of the multiple reference voltages as the voltage threshold.

[0011] Preferably, the three-state determination circuit includes a high threshold comparator and a low threshold comparator, and the three-state determination circuit is configured to: when the amplitude of the analog entropy voltage signal is higher than a high voltage threshold, output a first switching signal for reducing the injection rate of this unit; when the amplitude of the analog entropy voltage signal is lower than a low voltage threshold, output a second switching signal for extending the holding time of this unit.

[0012] Preferably, the physical coordination and health diagnosis unit further includes a fault determination unit, which is configured to determine the amplitude of the current ripple signal. with a fault amplitude threshold For comparison, the amplitude Above the fault amplitude threshold When the condition is met and the duration of the condition exceeds a fault duration threshold, a fault isolation signal is output; wherein, is the amplitude of the current ripple signal, is the fault amplitude threshold.

[0013] Preferably, the physical collaboration and health diagnosis unit is configured as follows: when the amplitude of the analog entropy voltage signal of a certain injection molding unit is higher than the high voltage threshold, a compensation current is output through a 4mA to 20mA current loop to an adjacent injection molding unit whose analog entropy voltage signal amplitude is neither higher than the high voltage threshold nor lower than the low voltage threshold; the compensation current is configured to be superimposed on the drive signal of the holding pressure control valve of the adjacent injection molding unit to increase the holding pressure of the adjacent injection molding unit.

[0014] Preferably, it further includes a central status monitoring unit, which is connected via an industrial bus; the central status monitoring unit is configured to receive a switch signal and a fault isolation signal, and is configured to display the operating status indicated by the switch signal and the warning information indicated by the fault isolation signal on a human-machine interaction interface; the central status monitoring unit is also configured to stop sending a compensation signal to the injection molding unit that generates the fault isolation signal and ignore the compensation signal received from the injection molding unit after receiving the fault isolation signal; the central status monitoring unit does not participate in real-time process decision-making.

[0015] Preferably, the hardware filter amplifier circuit is a combination of a differential amplifier circuit and a high-pass filter circuit, the differential amplifier circuit is configured to amplify the output signal of the differential pressure sensor, and the high-pass filter circuit is configured to filter out the low-frequency macro pressure component in the output signal of the differential amplifier circuit.

[0016] Preferably, the three-state determination circuit is implemented by two voltage comparators, the high voltage threshold and the low voltage threshold are determined by the reference voltage corresponding to the selection signal output by the threshold dynamic calibration module, and the output ends of the two voltage comparators are respectively connected to two solid-state relays for executing injection rate reduction and pressure holding time extension.

[0017] Preferably, the hardware bandpass filter is a passive bandpass filter composed of a resistor and a capacitor, and the predetermined frequency range of the hardware bandpass filter is 20 Hz to 200 Hz.

[0018] Preferably, the system is configured to work collaboratively in an injection molding cycle, and its working method includes: the threshold dynamic calibration module determines the voltage threshold based on the signal of the injection pressure change rate in the initial stage of injection molding; the entropy sensing unit generates an analog entropy voltage signal in the filling and holding stages; the three-state determination circuit adjusts the process parameters of this unit based on the analog entropy voltage signal and the determined voltage threshold; and the physical collaboration and health diagnosis unit monitors the current ripple signal to evaluate the health status of the actuator, and transmits the compensation signal between the injection molding units.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] 1. The present invention establishes a new injection molding process control method through the combination of an entropy sensing unit, a distributed self-balancing execution unit, and a physical collaboration and health diagnosis unit; wherein, the entropy sensing unit uses a hardware circuit to directly convert the microscopic pulsation in the pressure signal sensed at the injection nozzle into an analog entropy voltage signal that can instantly reflect the flow state of the polymer melt in the mold cavity. This method enables the control system to avoid relying on indirect inference of preset process parameters, and instead obtains the ability to directly perceive the actual flow state of the melt, thereby providing subsequent adjustment actions with real-time basis from the physical process itself, which is difficult to obtain in previous technologies.

[0021] 2. The present invention combines the analog entropy voltage signal generated by the entropy sensing unit with the threshold dynamic calibration function and the three-state judgment circuit in the distributed self-balancing execution unit; at the beginning of each injection molding cycle, the system uses the initial change rate characteristics of the injection pressure to first determine the control threshold suitable for the currently used material, and then in the filling and holding stages, the three-state judgment circuit will perform real-time evaluation of the analog entropy voltage signal based on this calibrated threshold, and directly drive the process parameters of this unit to adjust; the close connection of this series of actions enables the system to not only cope with flow fluctuations in the production process of a single material, but also automatically adjust its operating benchmark when facing changes in production boundary conditions such as material replacement, adapting to the actual needs of multi-material and flexible production of automotive interior panels.

[0022] 3. The present invention constructs an information multiplexing mechanism by carrying the physical coordination function and the diagnostic function of the actuator health status on the same 4mA to 20mA current loop. While the loop serves as a physical channel for transmitting compensation current between units, the ripple signal carried by the loop current itself, which is usually regarded as noise, is extracted by the hardware bandpass filter and used to evaluate the health status of the actuator. This design enables the system to obtain both process coordination control and equipment status self-diagnosis capabilities without adding additional sensors and information channels. When an actuator is diagnosed with an abnormal operation, the central status monitoring unit can logically isolate the unit, avoiding incorrect coordination due to actuator failure and improving the operational reliability of the entire management and control system. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a schematic diagram of the system architecture of an intelligent control system for the entire injection molding process of an automobile interior trim panel according to the present invention;

[0024] Figure 2 This is a schematic diagram of the operating effect of the fault diagnosis function of the physical collaboration and health diagnosis unit of the present invention;

[0025] Figure 3 This is an operation flow chart of an intelligent control system for the entire injection molding process of automobile interior trim panels according to the present invention. DETAILED DESCRIPTION

[0026] In order to make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. It should be noted that the embodiments in this application and the features in the embodiments can be combined with each other unless there is a conflict.

[0027] The present invention discloses an intelligent control system for the entire injection molding process of automobile interior trim panels, which includes an entropy sensing unit, a distributed self-balancing execution unit, and a physical coordination and health diagnosis unit, wherein the entropy sensing unit is configured to extract a signal representing the flow state of the melt from the physical signal of the injection molding machine; the distributed self-balancing execution unit adaptively adjusts the process parameters of the unit based on the signal and in combination with the online identification of the current physical properties of the material; the physical coordination and health diagnosis unit utilizes the same physical channel to achieve process compensation between units while diagnosing the physical health state of key actuators online. In addition, a central status monitoring unit is connected to each unit through an industrial bus for macroscopic monitoring of the status and logical isolation of faults, but does not participate in real-time process decision-making; in the injection molding application of large-scale thin-walled interior trim panels of automobiles, there is a technical challenge, that is, it is difficult to obtain the flow state of polymer melt inside a complex mold cavity in real time. To meet this challenge, this system The configured entropy sensing unit is arranged at the nozzle of an injection molding unit, and includes a pressure difference sensor and a hardware filtering and amplifying circuit connected to it. The hardware filtering and amplifying circuit is a combination of a differential amplifier circuit and a high-pass filter circuit. During the injection filling and holding pressure stages, the pressure difference sensor inputs the physical pressure signal at the nozzle into the circuit, and the differential amplifier circuit amplifies the pressure signal. Subsequently, the high-pass filter circuit is configured to filter out the low-frequency component in the signal that represents the pressure change, and only allow the pressure pulsation that can reflect the microscopic flow state of the melt to pass through. In this way, the output end of the hardware circuit generates an analog entropy voltage signal whose amplitude is modulated by the intensity of the microscopic pressure pulsation. The voltage amplitude of the signal corresponds to the degree of turbulence of the melt flowing in the mold cavity. Through this procedure based on physical effect conversion, the system obtains the ability to directly perceive the flow state of the polymer melt, providing a real-time basis for subsequent closed-loop regulation, where the response time is determined by the hardware circuit itself.

[0028] Furthermore, different types of plastic raw materials have different physical properties such as melt index and viscosity, which leads to different physical characteristic thresholds that characterize their flow instability. In view of this, the distributed self-balancing execution unit in this system is configured to perform a dynamic calibration of the control threshold at the initial stage of each injection molding cycle. It integrates a hardware differential circuit and a threshold dynamic calibration module. At the initial stage of the injection molding cycle, the injection pressure signal sensed by the aforementioned differential pressure sensor has an initial change rate of It is converted into a spike voltage signal by the hardware differential circuit. The amplitude of this signal is a physical representation of the current material's molten properties. A voltage comparator in the threshold dynamic calibration module then compares the amplitude of the spike voltage signal with multiple reference voltages stored inside the module and representing the standard pressure slopes of different reference materials. A selection signal is output based on the comparison result, and the voltage threshold suitable for the current injection molding material is determined from multiple reference voltages. This mechanism of determining the control benchmark in advance in the initial stage of injection molding enables the system to adapt to changes in production boundary conditions brought about by raw material replacement, and provides an operating benchmark corresponding to the current material's physical properties for subsequent process parameter adjustments.

[0029] After determining the voltage threshold suitable for the current material, the system needs to effectively intervene in the injection molding process to suppress molding defects. To this end, the distributed self-balancing execution unit also includes a three-state judgment circuit implemented by two voltage comparators. The input end of the circuit receives the analog entropy voltage signal generated by the entropy sensing unit and compares it with the high voltage threshold and low voltage threshold determined by the threshold dynamic calibration module. Specifically, when the amplitude of the analog entropy voltage signal is higher than a high voltage threshold, it indicates that the melt flow turbulence increases. At this time, the first comparator flips and outputs a first switching signal for reducing the injection rate of this unit. When the amplitude of the analog entropy voltage signal is lower than a low voltage threshold, it indicates that the melt flow tends to slow down. At this time, the second comparator flips and outputs a second switching signal for extending the holding time of this unit. The switching signal directly drives two solid-state relays to execute the reduction of the injection rate or the extension of the holding time at the hardware response speed. In this way, the system constructs a feedback loop based on the hardware circuit, which can suppress the flow instability trend before it develops into a defect.

[0030] In the multi-point casting of automobile interior panels, the local flow state of a single injection unit will affect the global molding quality. At the same time, the attenuation of the physical properties of the control system actuator after long-term operation will also pose a potential risk. To cope with this situation, this system has built a physical collaboration and health diagnosis unit. The unit uses a standard 4mA to 20mA current loop to transmit signals between multiple injection units. When the amplitude of the analog entropy voltage signal of a certain injection unit is higher than the high voltage threshold, in addition to performing its own parameter adjustment, the unit also transmits a signal to a unit whose analog entropy voltage signal amplitude is stable through the 4mA to 20mA current loop. The adjacent injection unit in the state outputs a compensation current, which is configured to be superimposed on the drive signal of the holding pressure control valve of the adjacent injection unit, so that the holding pressure of the adjacent injection unit increases accordingly. At the same time, a hardware bandpass filter connected in series with the 4mA to 20mA current loop is configured to extract a current ripple signal within a specific frequency range from the loop current. The predetermined frequency range of the hardware bandpass filter is set to 20 Hz to 200 Hz. This frequency band corresponds to the jitter frequency range generated when mechanical wear or jamming occurs to actuators such as hydraulic valves. A fault judgment unit calculates the amplitude of the current ripple signal. with a preset fault amplitude threshold For comparison, the amplitude Above the fault amplitude threshold When the condition is met and the duration of the condition exceeds a fault duration threshold, a fault isolation signal is output. When the central status monitoring unit receives the fault isolation signal, it stops sending compensation signals to the injection molding unit that generates the signal and ignores the compensation request received from it, thereby avoiding incorrect coordination caused by actuator failure and ensuring the operational reliability of the system.

[0031] During the initial deployment and calibration phase of the system, the transfer characteristics of the hardware filter amplifier circuit are determined by a transfer function The standard test process is solidified, is the complex frequency variable in the Laplace transform, and the function is characterized as a second-order Butterworth high-pass filter with a 3dB corner frequency Set it to 125.6rad / s, corresponding to 20Hz, and connect a series gain Linear amplification link, so that the input pressure pulsation signal The analog entropy voltage signal output Established between Unique mapping relationship; at the same time, the fingerprint voltage used to characterize the physical properties of a specific material , then the pressure change rate in the initial stage of at least 20 consecutive injection cycles is The peak voltage is collected and the arithmetic mean of the data is calculated after eliminating all outliers that are 1.5 times the interquartile range above and below the median. Here, the interquartile range is defined as the difference between the 75th and 25th percentiles of the sample data. The purpose of this procedure is to generate a material property benchmark with statistical robustness; the high voltage threshold of the three-state determination circuit With low voltage threshold The value is derived from an offline associative calibration procedure that first acquires surface point cloud data of a series of progressively filled samples through 3D optical scanning and calculates the root mean square deviation from the nominal CAD model to obtain a quantitative product quality indicator. , and then this The RMS value of the analog entropy voltage signal corresponding to each injection Perform function fitting, then It is determined as the inflection point on the fitting curve that represents the quality deterioration, that is, the quality index change rate When the absolute value of value, and is determined to produce the minimum The value is the best quality sample corresponding to 120% of the value; In addition, the fault amplitude threshold of the physical coordination and health diagnosis unit , is determined as the 99.7th percentile value of the 4mA to 20mA loop current ripple amplitude sample data collected during 100 healthy operating cycles, which statistically corresponds to the three sigma boundary in the normal distribution, while the fault duration threshold It is set to five times the maximum duration of any transient ripple event observed during the baseline acquisition period.

[0032] Example 1: In an injection molding unit for producing large-sized automobile door panels with a rib structure, after completing a batch of polypropylene material production tasks, the unit switches to an acrylonitrile-butadiene-styrene copolymer material with a different viscosity for production; after the switch, the door panels produced are identified to have continuous sink marks and weld mark defects in the rib-dense area away from the gate; when the next injection molding cycle is started, the system of the present invention starts to operate, and the hardware differential circuit in its distributed self-balancing execution unit captures the pressure signal output by the pressure difference sensor at the initial stage of injection molding and calculates its initial change rate. The module converts the peak voltage signal into a peak voltage signal; the threshold dynamic calibration module compares the amplitude of the peak voltage signal with the internally stored reference voltage representing the baseline pressure slope of the polypropylene material, and identifies a voltage deviation caused by a material change; accordingly, the module outputs a selection signal to automatically switch the high voltage threshold used by the three-state determination circuit from the reference voltage originally suitable for polypropylene material to a reference voltage preset for acrylonitrile-butadiene-styrene copolymer material.

[0033] In the subsequent filling and holding stages, when the melt flows in the mold cavity and encounters the obstruction of the reinforcing rib structure, its flow front becomes turbulent. The amplitude of the analog entropy voltage signal generated by the entropy sensing unit increases accordingly and reaches the high voltage threshold that has been dynamically calibrated. The high threshold comparator in the three-state judgment circuit is then flipped, and the output signal drives the solid-state relay to operate, temporarily reducing the injection rate of the injection molding unit by a small amount. This adjustment suppresses the turbulent trend of the melt flow, and the amplitude of the analog entropy voltage signal also drops back to between the high and low thresholds, after which the injection rate is restored. The connection of this series of actions, that is, the threshold dynamic calibration module, provides the subsequent three-state judgment circuit with a decision-making benchmark corresponding to the current material properties, and the three-state judgment circuit uses this benchmark to instantaneously adjust the flow instability caused by changes in material properties.

[0034] During the same production cycle, if the analog entropy voltage signal of an injection molding unit is continuously lower than the preset low voltage threshold due to local temperature fluctuations, indicating that it has filling hysteresis, the three-state judgment circuit of the unit outputs a signal to extend its own holding time. At the same time, its physical coordination and health diagnosis unit also outputs a compensation current to the adjacent injection molding unit operating in a stable state through a 4mA to 20mA current loop; this compensation current is superimposed on the drive signal of the holding pressure control valve of the adjacent unit, so that its holding pressure is automatically increased to assist in filling possible under-injection areas; this process does not rely on the central controller to recalculate and distribute parameters, but rather each distributed unit performs spontaneous collaborative compensation based on its own physical state and that of the adjacent units, converting the adjustment of process parameters into following and balancing the real-time flow state of the melt; after several autonomous operation of injection molding cycles, the incidence of shrinkage marks and weld mark defects in the rib-dense areas of the door panels continuously sampled from the production line has decreased, and the product quality stability has returned to the level before the material switch.

[0035] Example 2: In order to objectively verify the performance of the system of the present invention in dealing with fluctuations in the physical properties of raw materials and diagnosing the health status of actuators, the following comparative test was designed and performed. The test used a standard injection molding machine and a two-cavity mold for producing automobile air-conditioning outlet blades. The test materials were polypropylene material A as a reference material, and a polypropylene material B with the same main components but a melt index 10% higher. The test was divided into a control group and an experimental group. When the control group was running, the adaptive adjustment and diagnostic functions of the system of the present invention were disabled, and the injection molding machine was operated with fixed process parameters. When the experimental group was running, all functions of the system of the present invention were enabled.

[0036] A key parameter in the experiment is the fault amplitude threshold in the physical coordination and health diagnosis unit The technical consideration for its setting is to strike a balance between the sensitivity of detecting early faults and the ability to resist interference from normal operating noise. A too low threshold may cause false alarms due to background electromagnetic noise, while a too high threshold will delay the recognition of actuator performance degradation. For this reason, the setting procedure is determined to be to use an actuator in good health to run 10 injection cycles at the beginning of the test, and collect and calculate the average value of the current ripple signal amplitude in the 4mA to 20mA current loop during this period. , then the fault amplitude threshold Set to a specific multiple of the base value, i.e. In this test environment, the average value of the measured reference ripple amplitude is 0.02mA, so the fault amplitude threshold It is set to 0.1mA; the test first uses material A to run 200 cycles under the conditions of the control group and the experimental group respectively to establish a performance baseline, and then at the 201st cycle, the material is switched to material B and continued to run for 200 cycles. During this period, the molding defect rate of the product and the amplitude of the analog entropy voltage signal output by the entropy sensing unit are recorded. Some of the process data are shown in Table 1; Referring to Table 1, after switching to material B, the defect rate of the control group increased from 1.5% to 8.5%, and the average amplitude of its analog entropy voltage signal also increased from 4.1V to 7.8V; after switching materials, the defect rate of the experimental group stabilized at 1.6%, and the average amplitude of its analog entropy voltage signal remained at 4.3V, close to the baseline level; the reason for this phenomenon is that the threshold dynamic calibration module of the experimental group recognizes the initial change rate of injection pressure at the initial stage of each cycle The system detects the difference in the physical properties of material B and automatically adjusts the control threshold of the three-state judgment circuit. The latter then adjusts the injection process in real time based on this calibrated threshold, thereby suppressing the large fluctuations in flow state caused by material changes.

[0037] Table 1: Comparison of the operating status of the control group and the experimental group under different materials.

[0038]

[0039] In the 401st cycle, the orifice of a pressure-maintaining pressure control valve was fine-tuned to simulate an early mechanical hysteresis failure caused by sludge blockage. In the control group, this failure was not detected. In the experimental group, the current ripple signal amplitude extracted from the 4mA to 20mA current loop by the hardware bandpass filter of the physical coordination and health diagnosis unit was 0.0147mA in the 401st cycle. , the value is recorded as 0.13mA, which exceeds the preset fault amplitude threshold (0.1mA), and this state continues for more than the set fault duration threshold, then the fault judgment unit outputs a fault isolation signal to the central status monitoring unit, which then displays the warning information of the corresponding unit on the human-computer interaction interface.

[0040] Example 3: This example combines Figures 1 to 3 , to explain the implementation of an intelligent control system for the entire process of automobile interior panel injection molding, such as Figure 1 As shown in the figure, the figure includes an entropy sensing unit, a distributed self-balancing execution unit, a physical coordination and health diagnosis unit and a central status monitoring unit; the entropy sensing unit obtains the pressure signal from the pressure difference sensor at the nozzle of the injection unit, and after processing through the hardware filtering and amplifying circuit, generates an analog entropy voltage signal and transmits it to the distributed self-balancing execution unit; the distributed self-balancing execution unit receives the analog entropy voltage signal, and combines it with a signal generated by the hardware differential circuit to characterize the pressure change rate at the initial stage of injection molding, and finally outputs a switch signal to the solid-state relay that controls the injection rate and the holding time respectively through the threshold dynamic calibration module and the three-state judgment circuit; the physical coordination and health diagnosis unit receives the switch signal and uses a The current loop achieves the compensation current output while passing through a passband range of to The hardware bandpass filter and fault judgment unit extract and analyze the signal from the loop to generate a fault isolation signal; finally, the switch signal and the fault isolation signal are transmitted to the central status monitoring unit, which connects the human-machine interface and the industrial bus to realize macro-monitoring of the system.

[0041] like Figure 2 As shown in the figure, the relationship between the current ripple amplitude monitored by the physical coordination and health diagnosis unit and the preset fault threshold in the continuous injection cycle sequence is shown; the figure shows that before injection cycle 400, the measured value of the current ripple amplitude represented by the solid line is continuously and stably lower than the set value represented by the dotted line. Failure threshold , and after injection cycle 401, the amplitude value The phenomenon of rapidly climbing and continuously being above the fault threshold intuitively demonstrates that the unit can achieve online detection and early warning of potential operating faults by capturing the characteristic signal changes in the current loop when the actuator is working.

[0042] like Figure 3 As shown in the figure, after the system is started, it performs power-on self-test and parameter initialization, and then enters the stage of identifying the physical properties of the current production material, and performs dynamic threshold calibration based on the identification results; after the injection molding cycle starts, the system core enters a perception link consisting of entropy perception monitoring, pressure signal acquisition and processing, and analog entropy voltage signal generation. The signal is sent to the three-state judgment link. If the signal is within the normal range, the system operates normally and enters the physical collaborative compensation and actuator health diagnosis process. If the signal is higher than the threshold, the injection rate is reduced. If the signal is lower than the threshold, the holding time is extended. After these two adjustment actions are completed, the process is also merged into the actuator health diagnosis link; in the health diagnosis, if it is determined that there is no fault, the injection molding cycle is completed, and after central status monitoring, it is ready to enter the next cycle. If a fault is detected, the cycle is completed after the fault isolation signal is output.

[0043] Example 4: When the system of the present invention is installed for the first time in an injection molding unit and is planned to be used to produce an automotive interior panel product whose rheological properties are unknown, initial control parameters are set for the system, and an offline parameter calibration procedure can be performed to determine the high voltage threshold and low voltage threshold required by the three-state determination circuit; the initial state of the calibration procedure is to load the material to be calibrated into the injection molding machine that has completed the material cleaning, and make the mold temperature and melt temperature reach the stable process setting value recommended by the material supplier; at the beginning of the procedure, the system is operated in an open-loop monitoring mode, that is, the entropy sensing unit normally generates an analog entropy voltage signal, but the switch signal output of the three-state determination circuit is disabled, and the operator performs a set of progressive short shot fillings, starting with an injection volume of 30% of the mold volume, and gradually increasing the injection volume by 5% increments until the mold volume is filled to 95%. During each injection process, the data acquisition system synchronously records the complete waveform of the analog entropy voltage signal.

[0044] After each progressive filling is completed, the plastic parts are sampled and inspected to identify the critical samples where surface defects caused by unstable flow appear for the first time; then, the maximum peak voltage of the analog entropy voltage signal recorded during the filling stage of the sample without defects obtained in the previous injection is used as a reference, and the high voltage threshold is set to 90% of the peak value; at the same time, the low voltage threshold is set to 120% of the average voltage value of the relatively stable section of the voltage waveform during the same injection filling stage; while executing the above calibration procedures, the hardware differential circuit also works synchronously, and at the initial stage of each progressive short shot filling, it will generate a signal representing the injection pressure change rate. spike voltage signal; take the average amplitude of the spike voltage signal generated by multiple injections as a fingerprint voltage characterizing the molten physical properties of the material, and store the voltage value together with a code identifying the material in the reference voltage list of the threshold dynamic calibration module to expand its material database; if calibration is required for another new material, repeat this complete progressive filling and data analysis process; after the calibration procedure is completed, the system will have initial control parameters with a definite physical source for the new material, so that it can be effectively adaptively adjusted in subsequent batch production.

[0045] Example 5: In a production environment with multiple injection molding units of different specifications and pressure levels, in order to make the physical synergy function work effectively among different units, a synergy gain coefficient calibration procedure needs to be performed after the system is deployed. This procedure is performed for each pair of injection molding units with a physical synergy relationship. The operator first adjusts the process parameters temporarily to compensate for the output of the unit. Enter a state where the analog entropy voltage signal is higher than the high voltage threshold, and record the compensation current value output to the 4mA to 20mA current loop; at the same time, send the compensation current to the compensation receiving unit. A known small calibration current is superimposed on the holding pressure control valve drive signal and the change in holding pressure caused by it is measured; a dimensionless synergy gain coefficient is calculated based on the above measurement value , and store it in the system. This coefficient is used to adjust the unit in subsequent autonomous operation. Towards Unit The output compensation current is scaled so that the physical magnitude of the compensation action matches the pressure response characteristics of the receiving unit.

[0046] In the same calibration procedure, to ensure the stability of the health diagnostic function, a fault duration threshold must also be set. This threshold is designed to distinguish between true actuator performance degradation signals and transient electrical noise interference from the production environment. The operator runs the system at no load under a typical production cycle and uses a high-frequency current probe to monitor the 4mA to 20mA current loop, recording all amplitudes exceeding the fault amplitude threshold. The maximum duration of the instantaneous noise pulse ; Then the fault duration threshold Set to a specific multiple of the maximum noise duration, which is greater than 1. In this setting, the multiple is 3, that is, By following the above procedures, the physical coordination and health diagnostic functions of the system can operate in a predictable and consistent manner in a production environment consisting of multiple injection molding units with different physical dimensions and process parameters.

[0047] Example 6: Before the start of each production task after power-on, the system of the present invention is configured to automatically execute a power-on self-test and parameter initialization procedure to verify that its hardware units are in normal working condition and set a baseline value for the closed-loop regulation action; the procedure is initiated by the central status monitoring unit, which first inputs a preset weak voltage signal to the hardware filter amplifier circuit of the entropy sensing unit and reads the analog entropy voltage signal at its output end. If the reading is within the expected error range, it is confirmed that the path is working normally; then, the central status monitoring unit injects a test voltage higher than the high voltage threshold and a test voltage lower than the low voltage threshold into the input end of the three-state judgment circuit of each distributed self-balancing execution unit in turn, and reads back the switching status of the corresponding two solid-state relays via the industrial bus to confirm the functional integrity of the judgment circuit and the execution relay.

[0048] During this procedure, the system also verifies the parameters of the hardware filters. The hardware bandpass filter used for health diagnosis is designed to pass a predetermined frequency range of 20 Hz to 200 Hz. The parameter values ​​of its circuit components are determined based on the transfer function of a standard second-order passive bandpass filter, so that its center frequency is near the geometric mean of this passband, and the quality factor is set to achieve the required bandwidth. The next step in the procedure is to set the step size for the adjustment action of the three-state decision circuit. Based on the material type selected for the current production task, the system retrieves the corresponding injection rate adjustment and holding time adjustment from an internally stored control parameter matrix. This matrix is ​​generated by setting the injection rate adjustment to a specific percentage of the injection molding machine's current process setting and the holding time adjustment to a specific percentage of the holding-pressure duration. These percentages are determined based on offline experiments to effectively suppress flow fluctuations without causing process shock. This procedure verifies the physical integrity of the system before each production task begins and presets standardized adjustment steps for the control loop that match the process, thus forming the basis for stable system operation.

[0049] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An intelligent control system for the entire process of automobile interior panel injection molding, characterized in that: include: an entropy sensing unit, the entropy sensing unit comprising a differential pressure sensor disposed at a nozzle of an injection molding unit and a hardware filtering and amplifying circuit connected to the differential pressure sensor, the hardware filtering and amplifying circuit being configured to output, based on a pressure signal sensed by the differential pressure sensor, an analog entropy voltage signal whose amplitude is modulated by the intensity of microscopic pressure pulsations in the pressure signal; A distributed self-balancing execution unit, configured to receive an analog entropy voltage signal, includes a hardware differential circuit configured to generate a signal representing the injection pressure change rate during the initial phase of the injection molding cycle, and a threshold dynamic calibration module configured to determine a voltage threshold suitable for the current injection molding material from a plurality of reference voltages based on the injection pressure change rate signal. The distributed self-balancing execution unit also includes a three-state determination circuit configured to compare the analog entropy voltage signal with a voltage threshold and output a switching signal accordingly. The switching signal is used to control the injection rate and holding pressure parameters of the unit. A physical collaboration and health diagnosis unit, which includes a 4mA to 20mA current loop for transmitting signals between multiple injection molding units and a hardware bandpass filter connected in series with the 4mA to 20mA current loop. The hardware bandpass filter has a passband in a predetermined frequency range and is configured to extract a current ripple signal within the predetermined frequency range from the loop current of the 4mA to 20mA current loop.

2. The intelligent control system for the entire process of automobile interior panel injection molding according to claim 1 is characterized in that: The threshold dynamic calibration module includes a voltage comparator, which is configured to compare the signal representing the injection pressure change rate generated by the hardware differential circuit with multiple reference voltages representing the standard pressure slopes of different reference materials, and output a selection signal to the three-state determination circuit based on the comparison result to determine one of the multiple reference voltages as the voltage threshold.

3. The intelligent control system for the entire process of automobile interior panel injection molding according to claim 1 is characterized in that: The three-state determination circuit includes a high threshold comparator and a low threshold comparator. The three-state determination circuit is configured as follows: when the amplitude of the analog entropy voltage signal is higher than a high voltage threshold, the first switching signal is output to reduce the injection rate of the unit; when the amplitude of the analog entropy voltage signal is lower than a low voltage threshold, the second switching signal is output to extend the holding time of the unit.

4. The intelligent control system for the entire process of automobile interior panel injection molding according to claim 1 is characterized in that: The physical coordination and health diagnosis unit further includes a fault determination unit configured to determine the amplitude of the current ripple signal with a fault amplitude threshold For comparison, the amplitude Above the fault amplitude threshold When the condition is met and the duration of the condition exceeds a fault duration threshold, a fault isolation signal is output; wherein, is the amplitude of the current ripple signal, is the fault amplitude threshold.

5. The intelligent control system for the entire process of automobile interior panel injection molding according to claim 3 is characterized in that: The physical collaboration and health diagnosis unit is configured as follows: when the amplitude of the analog entropy voltage signal of a certain injection molding unit is higher than the high voltage threshold, a compensation current is output through a 4mA to 20mA current loop to an adjacent injection molding unit whose analog entropy voltage signal amplitude is neither higher than the high voltage threshold nor lower than the low voltage threshold; the compensation current is configured to be superimposed on the drive signal of the holding pressure control valve of the adjacent injection molding unit to increase the holding pressure of the adjacent injection molding unit.

6. The intelligent control system for the entire process of automobile interior panel injection molding according to claim 4 is characterized in that: The system further includes a central status monitoring unit connected via an industrial bus; the central status monitoring unit is configured to receive a switch signal and a fault isolation signal, and is configured to display an operating status indicated by the switch signal and a warning message indicated by the fault isolation signal on a human-machine interface; The central state monitoring unit is further configured to, after receiving the fault isolation signal, stop sending the compensation signal to the injection molding unit that generates the fault isolation signal and ignore the compensation signal received from the injection molding unit.

7. The intelligent control system for the entire process of automobile interior panel injection molding according to claim 1 is characterized in that: The hardware filter amplifier circuit is a combination of a differential amplifier circuit and a high-pass filter circuit. The differential amplifier circuit is configured to amplify the output signal of the differential pressure sensor, and the high-pass filter circuit is configured to filter out the low-frequency macro pressure component in the output signal of the differential amplifier circuit.

8. The intelligent control system for the entire process of automobile interior panel injection molding according to claim 3 is characterized in that: The three-state determination circuit is implemented using two voltage comparators. The high and low voltage thresholds are determined by the reference voltage corresponding to the selection signal output by the threshold dynamic calibration module. The output ends of the two voltage comparators are respectively connected to two solid-state relays used to reduce the injection rate and extend the pressure holding time.

9. The intelligent control system for the entire process of automobile interior panel injection molding according to claim 1 is characterized in that: The hardware band-pass filter is a passive band-pass filter composed of resistors and capacitors. The predetermined frequency range of the hardware band-pass filter is 20 Hz to 200 Hz.

10. The intelligent control system for the entire process of automobile interior panel injection molding according to claim 1, characterized in that: The system is configured to work collaboratively in an injection molding cycle, and its working method includes: the threshold dynamic calibration module determines the voltage threshold based on the injection pressure change rate signal in the initial stage of injection molding; the entropy sensing unit generates an analog entropy voltage signal during the filling and holding stages; the three-state determination circuit adjusts the process parameters of this unit based on the analog entropy voltage signal and the determined voltage threshold; and the physical coordination and health diagnosis unit monitors the current ripple signal to evaluate the health status of the actuator and transmits compensation signals between injection molding units.

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