An intelligent management and control system for the whole process of injection molding of an automotive interior panel

Abstract

The present application relates to the technical field of plastic injection molding, and discloses a full-process intelligent management and control system for injection molding of an automotive interior panel, comprising: an entropy sensing unit, which directly converts physical pressure pulsation at a nozzle into an analog entropy voltage signal; a distributed self-balancing execution unit, which adjusts process parameters adaptively according to the signal and in combination with an initial injection pressure change rate; and a physical coordination and health diagnosis unit, which realizes compensation between units and online assessment of the health state of an actuator by using the same current loop, wherein the present application avoids the dependence of a conventional control mode on preset parameters by establishing direct physical sensing of the flow state of a melt, and further realizes automatic adaptation to material changes and online diagnosis of the physical health of the system itself by analyzing sensing information in different dimensions, thereby improving the operation reliability of the injection molding process.

Description

TECHNICAL FIELD

[0001] The present application relates to a kind of automobile interior board injection molding whole process intelligent management and control system, belong to plastic injection molding technical field. BACKGROUND

[0002] Current in the injection molding of automobile interior board and other products, the prevailing technical method is to set a group of process parameters by control system, and maintain the constant of this group of process parameters in production cycle, the setting of this control method is based on ideal production condition, but the actual flow process of high polymer melt in mold cavity, and production boundary condition itself is dynamic change.

[0003] On the one hand, when the batch of raw materials used in production changes, its melting index and viscosity and other physical properties will also change, continue to use the original process parameter combination, will affect the forming quality, on the other hand, the actuator such as hydraulic valve in control system will be worn after long-term operation, resulting in deviation between its actual response and expected response to control command, and the control system lacks the monitoring approach to the deviation.

[0004] Specifically, the prior art mainly has the following deficiencies: 1. The control system lacks real-time physical sensing ability of the melt flow state in the mold cavity, leading to a lag in response to molding defects caused by flow instability; 2. The control system cannot identify subtle changes in material properties or sense the health status decay of key actuators online, making it difficult to achieve adaptive adjustment and proactive maintenance of dynamic production boundary conditions. Therefore, how to build an injection control system that not only can monitor the core flow state of the melt in real time, but also can identify material properties and assess the health status of its own actuator online, so as to realize closed-loop control from passive parameter execution to multi-dimensional state self-sensing, has become a technical problem to be solved by the present application. SUMMARY

[0005] The present application provides an automobile interior board injection molding whole process intelligent management and control system, which mainly aims to solve the problem that the existing injection control system cannot sense the melt flow state in real time, adapt to material changes and diagnose the health of the actuator online, resulting in limited control precision and operation reliability.

[0006] To achieve the above purpose, the present application provides an automobile interior board injection molding whole process intelligent management and control system, which comprises:

[0007] An entropy sensing unit, the entropy sensing unit comprises a differential pressure sensor arranged at the nozzle of an injection unit and a hardware filter amplification circuit connected with the differential pressure sensor, the hardware filter amplification circuit is configured to output an analog entropy voltage signal whose amplitude is modulated by the micro-pressure pulsation intensity in the pressure signal sensed by the differential pressure sensor based on the pressure signal sensed by the differential pressure sensor;

[0008] A distributed self-balancing execution unit configured to receive an analog entropy voltage signal, the distributed self-balancing execution unit comprising a hardware differentiation circuit configured to generate a signal representing a rate of change of injection pressure at an initial stage of an injection cycle and a threshold dynamic calibration module configured to determine a voltage threshold applicable to a current injection material from a plurality of reference voltages based on the signal representing the rate of change of injection pressure; the distributed self-balancing execution unit further comprising a tri-state decision circuit configured to compare the analog entropy voltage signal with the voltage threshold and output a switching signal based thereon, the switching signal being used to control an injection rate and a holding pressure parameter of the unit;

[0009] A physical coordination and health diagnosis unit comprising a 4mA to 20mA current loop for transmitting signals among a plurality of injection units and a hardware band-pass filter connected in series with the 4mA to 20mA current loop, the hardware band-pass filter having a passband of a predetermined frequency range and being configured to extract a current ripple signal in the predetermined frequency range from a loop current of the 4mA to 20mA current loop.

[0010] Preferably, the threshold dynamic calibration module comprises a voltage comparator configured to compare the signal representing the rate of change of injection pressure generated by the hardware differentiation circuit with a plurality of reference voltages each representing a standard pressure slope of a different reference material and output a selection signal to the tri-state decision circuit based on the comparison result to determine one of the plurality of reference voltages as the voltage threshold.

[0011] Preferably, the tri-state decision circuit comprises a high threshold comparator and a low threshold comparator, the tri-state decision circuit being configured to output a first switching signal used to reduce the injection rate of the unit when the amplitude of the analog entropy voltage signal is higher than a high voltage threshold and output a second switching signal used to extend the holding pressure time of the unit when the amplitude of the analog entropy voltage signal is lower than a low voltage threshold.

[0012] Preferably, the physical coordination and health diagnosis unit further comprises a fault decision unit configured to compare the amplitude of the current ripple signal with a fault amplitude threshold, output a fault isolation signal when the amplitude of the current ripple signal is higher than the fault amplitude threshold and the condition is satisfied and the duration of the condition exceeds a fault duration threshold; wherein, is the amplitude of the current ripple signal, is the fault amplitude threshold.

[0013] ​​​​Preferably, the physical coordination and health diagnosis unit is configured to output a compensation current to an adjacent injection molding unit through a 4mA to 20mA current loop when the amplitude of the analog entropy voltage signal of a certain injection molding unit is higher than the high voltage threshold value, the compensation current is configured to be superimposed on the drive signal of the pressure maintaining pressure control valve of the adjacent injection molding unit to increase the pressure maintaining pressure of the adjacent injection molding unit.

[0014] Preferably, a central state monitoring unit is further included, the central state monitoring unit is connected through the industrial bus; the central state monitoring unit is configured to receive the switch signal and the fault isolation signal, and is configured to display the running state indicated by the switch signal and the early warning information indicated by the fault isolation signal on the human-computer interaction interface; the central state monitoring unit is further configured to stop sending the compensation signal to the injection molding unit generating the fault isolation signal and to ignore the compensation signal received from the injection molding unit after receiving the fault isolation signal; the central state monitoring unit does not participate in real-time process decision-making.

[0015] Preferably, the hardware filter amplification circuit is a combination of a differential amplification circuit and a high-pass filter circuit, the differential amplification circuit is configured to amplify the output signal of the pressure difference 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 amplification circuit.

[0016] Preferably, the tri-state determination circuit is implemented by two voltage comparators, the high voltage threshold value and the low voltage threshold value are determined by the reference voltages corresponding to the selection signals 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 maintaining time extension.

[0017] Preferably, the hardware band-pass filter is a passive band-pass filter composed of resistors and capacitors, and the predetermined frequency range of the hardware band-pass filter is 20Hz to 200Hz.

[0018] Preferably, the system is configured to work cooperatively in an injection molding cycle, and the working mode includes: the threshold dynamic calibration module determines the voltage threshold value based on the signal of the injection pressure change rate in the initial stage of injection molding; the entropy perception unit generates an analog entropy voltage signal in the filling and pressure maintaining stage; the tri-state determination circuit adjusts the process parameters of the unit according to the analog entropy voltage signal and the determined voltage threshold value; and the physical coordination 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 beneficial effects of the present application are:

[0020] 1. The application establishes a new injection molding process control mode through the combination of an entropy sensing unit, a distributed self-balancing execution unit, and a physical cooperation and health diagnosis unit. The entropy sensing unit uses a hardware circuit to directly convert the microscopic pulsations in the pressure signal sensed at the injection nozzle into an analog entropy voltage signal that can immediately reflect the flow state of the polymer melt in the mold cavity. This approach enables the control system to avoid indirect inference based on pre-set process parameters and instead provides direct sensing of the real flow state of the melt, thereby providing real-time basis derived from the physical process itself for subsequent adjustment actions.

[0021] 2. The application 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 cycle, the system determines the control threshold suitable for the current material based on the initial rate of change of the injection pressure, and then the three-state judgment circuit judges the analog entropy voltage signal in real time based on the calibrated threshold and directly drives the adjustment of the process parameters in this unit. The close connection of this series of actions enables the system to not only handle flow fluctuations in single-material production processes, but also automatically adjust its operating reference when facing material replacement, a change in production boundary conditions, thereby meeting the actual needs of multi-material and flexible production of automotive interior panels.

[0022] 3. The application constructs an information multiplexing mechanism by loading the physical cooperation function and the diagnosis function of the actuator health status on the same 4mA to 20mA current loop. The loop serves as a physical channel for transferring compensation current between units, and at the same time, the ripple signal usually considered as noise carried by the loop current is extracted by a hardware band-pass filter and used to evaluate the health status of the actuator. This design enables the system to simultaneously obtain process cooperation control and device state self-diagnosis capabilities without adding additional sensors and information channels. When an abnormal operation of the actuator is diagnosed, the central state monitoring unit can logically isolate the unit, avoiding errors caused by actuator failure, and improving the operational reliability of the entire control system. BRIEF DESCRIPTION OF DRAWINGS

[0023] Fig. 1 The system architecture diagram of the application, an intelligent control system for the whole process of injection molding of automotive interior panels;

[0024] Fig. 2 The running effect diagram of the fault diagnosis function of the physical cooperation and health diagnosis unit of the application;

[0025] Fig. 3 The running flowchart of the application, an intelligent control system for the whole process of injection molding of automotive interior panels. DETAILED DESCRIPTION

[0026] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described in detail below with reference to the drawings. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. It should be explained that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0027] The application discloses a kind of intelligent management and control systems of automobile interior plate injection molding full process, the system includes one entropy perception unit, one distributed self-balancing execution unit and one physical coordination and health diagnosis unit, wherein, entropy perception unit is configured to extract signal from injection molding machine physical signal, which represents the flow state of melt;Distributed self-balancing execution unit is combined with the online identification of current material physical properties according to the signal, and the process parameters of this unit are self-adaptive adjusted;Physical coordination and health diagnosis unit utilizes the same physical channel, realizes process compensation between units while diagnosing the physical health state of key actuator online, in addition, a central state monitoring unit is connected with each unit through industrial bus, for the macroscopic monitoring of state and the logical isolation of fault, but not participate in real-time process decision;In the injection molding application of automobile large thin-walled interior plate, there is a technical challenge, i.e. it is difficult to obtain the flow state of high polymer melt inside complex mold cavity in real time, to cope with this challenge, the entropy perception unit configured by the system is arranged at the nozzle of an injection unit, which includes a differential pressure sensor and a hardware filter amplification circuit connected therewith, the hardware filter amplification circuit is a combination of differential amplification circuit and high-pass filter circuit, during injection filling and pressure maintaining stage, the differential pressure sensor inputs the physical pressure signal at the nozzle to the circuit, the differential amplification circuit amplifies the pressure signal, then, the high-pass filter circuit is configured to filter out the low-frequency component in the signal representing pressure change, and only allows the pressure pulsation reflecting the micro flow state of melt to pass, in this way, the output end of the hardware circuit generates an analog entropy voltage signal, the amplitude of which is modulated by the micro pressure pulsation intensity, the voltage amplitude of the signal has corresponding relationship with the turbulence degree of melt flow in mold cavity;Through this rule based on physical effect conversion, the system obtains the direct perception ability of the flow state of high polymer melt, which provides real-time basis for subsequent closed-loop regulation, and 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 flow index and viscosity, resulting in different physical characteristic thresholds characterizing their flow instability. Therefore, the distributed self-balancing execution unit in this system is configured to perform dynamic calibration of the control threshold at the initial stage of each injection molding cycle. It integrates a hardware differentiating circuit and a threshold dynamic calibration module. At the initial stage of the injection molding cycle, the initial rate of change of the injection pressure signal sensed by the aforementioned differential pressure sensor... The signal is converted into a spike voltage signal by the hardware differentiating circuit. The amplitude of this signal is a physical characterization of the current material melt properties. A voltage comparator in the threshold dynamic calibration module then compares the amplitude of this spike voltage signal with multiple reference voltages stored internally by the module, representing the standard pressure slope of different reference materials. Based on the comparison result, a selection signal is output to determine the voltage threshold applicable to the current injection molding material from the multiple reference voltages. This mechanism of determining the control benchmark in advance at the initial stage of injection molding enables the system to adapt to changes in production boundary conditions caused by changes in raw materials, providing an operating benchmark corresponding to the current material 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 determination circuit implemented by two voltage comparators. The input of this circuit receives the simulated 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 simulated entropy voltage signal is higher than a high voltage threshold, it indicates that the melt flow turbulence has increased. At this time, the first comparator flips and outputs a first switching signal to reduce the injection rate of this unit. When the amplitude of the simulated 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 to extend the holding time of this unit. The switching signal directly drives two solid-state relays to reduce the injection rate or extend the holding time with hardware response speed. In this way, the system constructs a feedback loop based on hardware circuits, which can suppress the flow instability trend before it develops into a defect.

[0030] In multi-point casting of automotive interior panels, the local flow state of a single injection unit can affect the overall molding quality. Simultaneously, the degradation of the physical performance of the control system actuators after long-term operation poses a potential risk. To address this, this system incorporates a physical coordination and health diagnostic unit. This unit utilizes 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 exceeds a high-voltage threshold, in addition to adjusting its own parameters, the unit also transmits signals through the 4mA to 20mA current loop to a unit whose analog entropy voltage signal amplitude is stable. The adjacent injection molding unit outputs a compensation current, which is configured to be superimposed on the drive signal of the holding pressure control valve of the adjacent injection molding unit, thereby increasing the holding pressure of the adjacent injection molding unit accordingly. Simultaneously, a hardware bandpass filter connected in series with a 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 this hardware bandpass filter is set to 20 Hz to 200 Hz, which corresponds to the frequency range of vibrations generated when actuators such as hydraulic valves experience mechanical wear or jamming. A fault determination unit determines the amplitude of this current ripple signal. With a preset fault amplitude threshold Comparison, in 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 will stop sending compensation signals to the injection molding unit that generated the signal and ignore the compensation requests received from it, thereby avoiding erroneous coordination caused by actuator failure and ensuring the reliability of system operation.

[0031] During the initial deployment and calibration phase of the system, the transfer characteristics of the hardware filter amplifier circuit are determined by its transfer function as follows: The standard testing process is solidified, in which The function represents a complex frequency variable in the Laplace transform, and is characterized as a second-order Butterworth high-pass filter with a 3dB angular frequency. Set at 125.6 rad / s, corresponding to 20 Hz, and connected in series with a gain of The linear amplification stage enables the input pressure pulsation signal to be amplified. With the output analog entropy voltage signal A connection was established between them. A uniquely determined mapping relationship; simultaneously, fingerprint voltages used to characterize the physical properties of specific materials. Then, by analyzing the pressure change rate during the initial stage of at least 20 consecutive injection molding cycles... Peak voltages are collected, and the arithmetic mean of the data set is calculated after removing all outliers located 1.5 times above and below the median. Here, the interquartile range is defined as the difference between the 75th and 25th percentiles of the sample data. This procedure aims to generate a statistically robust material property benchmark. The high-voltage threshold of the three-state determination circuit... With low voltage threshold Its value originates from an offline correlation calibration procedure, which first acquires surface point cloud data of a series of progressively filled samples through 3D optical scanning, and calculates the root mean square deviation between the data and the nominal CAD model, thereby obtaining a quantitative product quality index. Then this The root mean square value of the analog entropy voltage signal corresponding to each injection. If function fitting is performed, then This was identified as the inflection point on the fitted curve that characterizes quality deterioration, i.e., the rate of change of the quality index. When the absolute value first exceeds the preset deterioration slope Value, and It is then determined to produce the minimum The value corresponding to the best quality sample The value is 120%; in addition, the fault amplitude threshold of the physical coordination and health diagnosis unit. The value was determined to be the 99.7th percentile of the loop current ripple amplitude sample data collected in 100 healthy operating cycles from 4mA to 20mA. This value statistically corresponds to the three sigma boundary of a normal distribution, while the fault duration threshold... It is then 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 automotive door panels with a ribbed structure, after completing a batch of polypropylene material production, the unit switches to an acrylonitrile-butadiene-styrene copolymer material with a different viscosity. After the switch, continuous shrinkage marks and weld lines were identified in the densely reinforced areas of the door panels far from the gate. At the start of the next injection molding cycle, the system of this invention begins operation. The hardware differential circuit within its distributed self-balancing execution unit captures the pressure signal output by the differential pressure sensor in the initial stage of injection molding and measures its initial rate of change. The peak voltage signal is converted into a peak voltage signal; the threshold dynamic calibration module compares the amplitude of the peak voltage signal with the reference voltage stored internally, which represents the reference pressure slope of the polypropylene material, and identifies a voltage deviation caused by material change; accordingly, the module outputs a selection signal to automatically switch the high voltage threshold used by the three-state judgment circuit from the reference voltage originally applicable to polypropylene material to a reference voltage preset for acrylonitrile-butadiene-styrene copolymer material.

[0033] During the subsequent filling and holding phase, when the melt flows in the cavity and encounters the obstruction of the rib structure, the flow front becomes turbulent, the amplitude of the simulated entropy voltage signal generated by the entropy sensing unit increases, and reaches the high voltage threshold that has been dynamically calibrated, the high threshold comparator in the three-state judgment circuit flips immediately, and the output signal drives the solid-state relay to act, temporarily reducing the injection rate of the injection unit by a small amount; this adjustment suppresses the turbulence trend of the melt flow, and the amplitude of the simulated entropy voltage signal also falls between the high and low thresholds, and then the injection rate returns to normal; the connection of this series of actions, i.e. the threshold dynamic calibration module provides the decision-making reference corresponding to the current material properties for the subsequent three-state judgment circuit, and the three-state judgment circuit adjusts the flow instability caused by the change of material properties in real time based on this reference.

[0034] In the same production cycle, if the simulated entropy voltage signal of a certain injection unit continuously falls below the preset low voltage threshold due to local temperature fluctuations, indicating that there is filling delay, the three-state judgment circuit of the unit extends its holding time through the output signal, and at the same time, its physical coordination and health diagnosis unit also outputs a compensation current to the adjacent injection unit working in a stable state through the 4mA to 20mA current loop; the compensation current is superimposed on the drive signal of the holding pressure control valve of the adjacent unit, causing the holding pressure to automatically increase to assist in filling the possible underfill area; this process does not rely on the central controller to recalculate and issue parameters, but relies on each distributed unit to compensate spontaneously based on its own and adjacent unit's physical state, converting the adjustment of process parameters into following and balancing the real-time flow state of the melt; after several independent runs of the injection cycle, the shrinkage and weld line defect rate in the dense rib area of the continuously sampled door panel products from the production line is reduced, and the product quality stability returns to the level before the material switch.

[0035] Example 2: To objectively verify the performance of the system in dealing with raw material property fluctuation and diagnosing the health status of the actuator, 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 conditioner outlet blade. The test materials were polypropylene material A as the benchmark material and polypropylene material B with the same main components but a 10% higher melt index. The test was divided into a control group and an experimental group. When the control group was running, the adaptive adjustment and diagnosis functions of the system were disabled, and the injection molding machine ran with fixed process parameters. When the experimental group was running, all functions of the system were enabled.

[0036] In the test, one key parameter was the fault amplitude threshold value in the physical synergy and health diagnosis unit . The technical consideration for its setting was to balance the detection sensitivity of early faults and the anti-interference ability to normal operation noise. A too low threshold value might produce false positives due to background electromagnetic noise, while a too high threshold value would delay the identification of actuator performance degradation. Therefore, its setting procedure was determined as follows: at the beginning of the test, a well-performing actuator was used to run for 10 injection molding cycles, and the average value of the current ripple signal amplitude in the 4mA to 20mA current loop during this period was calculated . Then the fault amplitude threshold value was set to a certain multiple of this benchmark value, i.e. . In this test environment, the measured average value of the benchmark ripple amplitude was 0.02mA, so the fault amplitude threshold value was set to 0.1mA. The test first used material A to run 200 cycles under the conditions of the control group and the experimental group respectively to establish the performance baseline, and then switched to material B at the 201st cycle and continued to run for 200 cycles. During this period, the product molding defect rate and the analog entropy voltage signal amplitude output by the entropy perception unit were recorded, and part of the process data is 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 the 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 the analog entropy voltage signal maintained at 4.3V, close to the baseline level. The reason for this phenomenon was that the threshold dynamic calibration module of the experimental group identified the change in the physical properties of material B by recognizing the difference in the initial change rate of injection pressure at the initial stage of each cycle, and automatically adjusted the control threshold of the three-state judgment circuit. The latter then adjusted the injection process in real time based on the calibrated threshold, thereby suppressing the large fluctuations in flow state caused by the change in materials.

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

[0038]

[0039] In the 401st cycle, a fine-tuning of the orifice of a pressure-holding control valve was performed to simulate an early mechanical lag failure caused by sludge blockage. In the control group, this failure was undetectable. In the experimental group, the amplitude of the current ripple signal extracted from the 4mA to 20mA current loop by the hardware bandpass filter of the physical coordination and health diagnostic unit in the 3rd cycle after the failure occurred was measured. Its value was recorded as 0.13mA, which exceeded the preset fault amplitude threshold. (0.1mA), and this state continues to exceed the set fault duration threshold. Subsequently, the fault determination unit outputs a fault isolation signal to the central status monitoring unit, which then displays the corresponding unit's warning information on the human-machine interface.

[0040] Example 3: This example combines Figs. 1 to 3 This document describes the implementation of an intelligent control system for the entire injection molding process of automotive interior panels. Fig. 1 As shown, the diagram includes an entropy sensing unit, a distributed self-balancing execution unit, a physical coordination and health diagnosis unit, and a central state monitoring unit. The entropy sensing unit acquires pressure signals from a differential pressure sensor at the injection unit nozzle. After processing by a hardware filtering and amplification circuit, it generates an analog entropy voltage signal and sends it to the distributed self-balancing execution unit. This distributed self-balancing execution unit receives the analog entropy voltage signal and combines it with a signal generated by a hardware differentiating circuit, representing the rate of pressure change during the initial injection phase. Through a threshold dynamic calibration module and a three-state determination circuit, it finally outputs a switch signal to solid-state relays that control the injection rate and holding time, respectively. The physical coordination and health diagnosis unit receives this switch signal and utilizes a... The current loop, while achieving compensated current output, also utilizes a passband range of... to The hardware bandpass filter and fault determination unit extract and analyze signals from the loop to generate fault isolation signals. Finally, the switching signals and fault isolation signals are transmitted to the central status monitoring unit, which connects the human-machine interface and the industrial bus to realize macro-level monitoring of the system.

[0041] like Fig. 2 As shown in the figure, this graph characterizes the relationship between the current ripple amplitude monitored by the physical coordination and health diagnostic unit and the preset fault threshold in consecutive injection molding cycles. The figure shows that before injection molding cycle 400, the measured value of the current ripple amplitude, represented by the solid line, is consistently and stably lower than the set value, represented by the dashed line. Fault threshold However, after injection molding cycle 401, this amplitude value... The rapid rise and sustained above the fault threshold, this phenomenon intuitively shows that the unit can capture the characteristic signal changes in the current loop when the actuator works, so as to realize the online detection and early warning of potential operation failure.

[0042] As Fig. 3 shown, the system starts after the power-on self-test and parameter initialization, and then enters the physical property identification stage of the current production material, and executes dynamic threshold calibration according to the identification result; After the injection molding cycle starts, the system core enters a sensing link composed of entropy sensing monitoring, pressure signal acquisition and processing, and simulated entropy voltage signal generation. The signal is sent to the three-state judgment link. If the signal is in the normal range, the system will run normally and enter 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 pressure time is extended. After the two adjustment actions are completed, the process also converges into the actuator health diagnosis link. In the health diagnosis, if no fault is found, the injection molding cycle is completed, and after the central state monitoring, it is ready to enter the next cycle. If a fault is detected, the cycle is completed after outputting the fault isolation signal.

[0043] Example 4: When an injection molding unit is first installed with the system of the present application and plans to produce a car interior panel product whose rheological properties are unknown, the initial control parameters of the system are set, and an offline parameter calibration procedure can be performed to determine the high voltage threshold and low voltage threshold required by the three-state judgment circuit; The initial state of the calibration procedure is to load the material to be calibrated in the injection molding machine that has completed the material cleaning, and the mold temperature and melt temperature are both set to the stable process setting value recommended by the material supplier; At the beginning of the procedure, the system works in an open-loop monitoring mode, that is, the entropy sensing unit normally generates a simulated entropy voltage signal, but the switch signal output of the three-state judgment circuit is disabled. The operator performs a set of progressive short shots, starting with an injection amount of 30% of the mold volume, increasing the injection amount by 5% each time, until filling to 95% of the mold volume. During each injection process, the data acquisition system synchronously records the complete waveform of the simulated entropy voltage signal.

[0044] After each progressive filling, the plastic part is sampled and inspected to identify the critical sample where surface defects caused by flow instability first appear. Then, using the maximum peak voltage of the simulated entropy voltage signal recorded during the filling stage of the previous defect-free sample as a benchmark, the high voltage threshold is set to 90% of this peak value. Simultaneously, using the average voltage value of the relatively stable voltage waveform segment within the same injection filling stage as a benchmark, the low voltage threshold is set to 120% of this average value. While executing the above calibration procedure, the hardware differentiating circuit also operates synchronously, generating a characterizing injection pressure change rate at the initial stage of each progressive short-shot filling. The system generates a spike voltage signal; the average amplitude of the spike voltage signal generated by multiple injections is taken as a fingerprint voltage characterizing the melt properties of the material, and this voltage value, along with a code identifying the material, is stored in the reference voltage list of the threshold dynamic calibration module to expand its material database; if calibration is required for another new material, this complete progressive filling and data analysis process is repeated; after this calibration procedure is completed, the system has initial control parameters with a definite physical origin for the new material, enabling it to effectively adaptively adjust in subsequent mass production.

[0045] Example 5: In a production environment containing multiple injection molding units with varying specifications and pressure ratings, to ensure the effective operation of the physical coordination function across different units, a calibration procedure for the coordination gain coefficient must be performed after system deployment. This procedure is applied to each pair of injection molding units with a physical coordination relationship. Operators first adjust the process parameters temporarily to compensate for the loss of the injection molding unit. The system enters a state where the simulated entropy voltage signal is higher than the high voltage threshold, and records the amount of compensation current output to the 4mA to 20mA current loop; simultaneously, it sends a signal to the compensation receiving unit. A known small-amplitude calibration current is superimposed on the pressure holding control valve drive signal, and the resulting change in pressure holding is measured; based on the above measurements, a dimensionless cooperative gain coefficient is calculated. This coefficient is stored in the system and used to adjust the unit's parameters during subsequent autonomous operation. To unit The emitted compensation current is scaled to match the physical magnitude of the compensation effect with the pressure response characteristics of the receiving unit.

[0046] In the same calibration procedure, a fault duration threshold is also set to ensure the stability of the health diagnosis function, which is intended to distinguish the real actuator performance degradation signal from the transient electrical noise disturbance from the production environment. The operator runs the system in an idle mode at a typical production pace and monitors the 4-20 mA current loop using a high frequency current probe, recording the longest duration of all transient noise pulses with amplitude exceeding the fault amplitude threshold ; then the fault duration threshold is set to a certain multiple of the maximum noise duration, which is greater than 1, in this case the multiple is 3, i.e. ; by performing the above procedure, the system can run in a predictable and consistent manner in a production environment consisting of multiple injection molding units with different physical sizes and process parameters, both in terms of physical coordination and health diagnosis function.

[0047] Example 6: Before the start of each production task after power-on, the system of the present application is configured to automatically perform a power-on self-test and parameter initialization procedure to verify that its hardware units are in normal working condition and set the reference values for closed-loop regulation actions; the procedure is initiated by the central state monitoring unit, which first inputs a pre-set weak voltage signal to the hardware filter amplifier circuit of the entropy sensing unit and reads the analog entropy voltage signal at its output, if the reading is within the expected error range, it confirms that the path is working normally; then the central state monitoring unit successively injects a test voltage higher than the high voltage threshold and a test voltage lower than the low voltage threshold to the input of the three-state judgment circuit of each distributed self-balancing execution unit, and reads back the switch state 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] ​In the procedure, the system also checks the parameters of the hardware filter, wherein the hardware band-pass filter for health diagnosis is designed to pass a predetermined frequency range of 20-200 Hz, the parameter values of the circuit elements are determined according to the transfer function of a standard second-order passive band-pass filter, so that the center frequency is located near the geometric mean of the passband, and the quality factor is set to obtain the required bandwidth; The next step of the procedure is to set the step size for the adjustment action of the three-state judgment circuit, and the system retrieves the corresponding injection rate adjustment amount and holding time adjustment amount from an internal control parameter matrix according to the material type selected by the current production task; The generation method of the matrix is to set the injection rate adjustment amount as a certain percentage of the current process setting value of the injection molding machine, and set the holding time adjustment amount as a certain percentage of the holding time; The percentage is a value determined based on offline experiments that can effectively suppress flow fluctuations without causing process impact; The execution of the procedure verifies the integrity of the physical layer of the system before each production task starts, and presets the standardized adjustment step size for the control loop that matches the process, thereby laying the foundation for the stable operation of the system.

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

[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting, although the present application 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 application can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. An intelligent management and control system for the whole process of injection molding of automotive interior panels, characterized in that, The application comprises: an entropy sensing unit, the entropy sensing unit comprising a differential pressure sensor arranged at a nozzle of an injection molding unit and a hardware filter-amplifier circuit connected to the differential pressure sensor, the hardware filter-amplifier circuit being configured to output an analog entropy voltage signal whose amplitude is modulated by the intensity of micro-pressure pulsations in a pressure signal sensed by the differential pressure sensor; a distributed self-balancing execution unit, the distributed self-balancing execution unit being configured to receive the analog entropy voltage signal, the distributed self-balancing execution unit comprising a hardware differentiation circuit configured to generate a signal representing the rate of change of injection pressure at the initial stage of an injection cycle and a threshold dynamic calibration module configured to determine a voltage threshold suitable for the current injection material from a plurality of reference voltages according to the signal representing the rate of change of injection pressure; the distributed self-balancing execution unit further comprising a tri-state decision circuit configured to compare the analog entropy voltage signal with the voltage threshold and output a switching signal accordingly, the switching signal being used to control the injection rate and the holding pressure parameters of the unit; a physical coordination and health diagnosis unit, the physical coordination and health diagnosis unit comprising a 4mA-20mA current loop for transmitting signals between a plurality of injection molding units and a hardware band-pass filter connected in series to the 4mA-20mA current loop, the hardware band-pass filter having a passband of a predetermined frequency range and being configured to extract a current ripple signal in the predetermined frequency range from the loop current of the 4mA-20mA current loop; the tri-state decision circuit comprises a high threshold comparator and a low threshold comparator, the tri-state decision circuit being configured to output a first switching signal for reducing the injection rate of the unit when the amplitude of the analog entropy voltage signal is higher than a high voltage threshold and output a second switching signal for extending the holding pressure time of the unit when the amplitude of the analog entropy voltage signal is lower than a low voltage threshold; the physical coordination and health diagnosis unit is configured to output a compensation current to an adjacent injection molding unit whose amplitude of the analog entropy voltage signal is neither higher than the high voltage threshold nor lower than the low voltage threshold through the 4mA-20mA current loop when the amplitude of the analog entropy voltage signal of a certain injection molding unit is higher than the high 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.

2. The intelligent management and control system for the whole injection molding process of an automotive interior panel according to claim 1, characterized in that, the threshold dynamic calibration module comprises a voltage comparator configured to compare the signal representing the rate of change of injection pressure generated by the hardware differentiation circuit with a plurality of reference voltages respectively representing standard pressure slopes of different reference materials, and output a selection signal to the tri-state decision circuit according to the comparison result to determine one of the plurality of reference voltages as the voltage threshold.

3. The intelligent management and control system for the whole injection molding process of an automotive interior panel according to claim 1, characterized in that, The physical collaboration and health diagnosis unit further comprises a fault determination unit configured to compare the amplitude of the current ripple signal to a fault amplitude threshold and output a fault isolation signal if the condition that the amplitude of the current ripple signal is higher than the fault amplitude threshold is met and the condition is sustained for more than a fault duration threshold; wherein is the amplitude of the current ripple signal, is the fault amplitude threshold.

4. The intelligent management and control system for the whole injection molding process of an automotive interior panel according to claim 3, characterized in that, a central state monitoring unit is further included, the central state monitoring unit being connected through an industrial bus; the central state monitoring unit being configured to receive the switching signal and the fault isolation signal, and being configured to display the running state indicated by the switching signal and the early warning information indicated by the fault isolation signal on a human-machine interface. The central state monitoring unit is further configured to stop sending compensation signals to the injection unit that generated the fault isolation signal and to ignore compensation signals received from the injection unit upon receiving the fault isolation signal.

5. The intelligent management and control system for the whole injection molding process of an automotive interior panel according to claim 1, characterized in that, The hardware filter amplification circuit is a combination of a differential amplification circuit and a high-pass filter circuit, the differential amplification circuit is configured to amplify the output signal of the pressure difference 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 amplification circuit.

6. The intelligent management and control system for the whole injection molding process of an automotive interior panel according to claim 1, characterized in that, The tri-state determination circuit is realized 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 maintaining time extension.

7. The intelligent management and control system for the whole injection molding process of an automotive interior panel according to claim 1, characterized in that, The hardware band-pass filter is a passive band-pass filter composed of resistors and capacitors, and the predetermined frequency range of the hardware band-pass filter is 20 Hz to 200 Hz. 8.The intelligent management and control system for the whole injection molding process of an automotive interior panel of claim 1, characterized in that, The system is configured to work cooperatively in an injection cycle, and the working mode 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; the entropy sensing unit generates an analog entropy voltage signal in the filling and pressure maintaining stage; the tri-state determination circuit adjusts the process parameters of the unit according to the analog entropy voltage signal and the determined voltage threshold; and the physical cooperation 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 units.

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