A multi-layer composite material intelligent mold visual platform system and its manufacturing method

Abstract

The present invention belongs to the field of injection molding process control technology, and in particular to a multi-layer composite material intelligent mold visual platform system and a manufacturing method thereof. The system includes a modular layered mold, each layer of which is provided with an independent temperature control unit and an electromagnetic compensation ejector pin; it also includes a multi-physics field sensor module that integrates temperature, pressure and vibration sensors to monitor the process parameters of the mold closing, injection molding and cooling stages in real time; it also includes a visual quality inspection module that includes a linear array camera and a laser displacement sensor for online detection of interlayer defects and dimensional tolerances; it also includes a control platform that dynamically optimizes process parameters based on sensor and visual data, and interacts with external management system data; the present invention can achieve dynamic compensation of interlayer pressure and temperature zoning control, solving the problem that traditional molds cannot adapt to deformation caused by thermal expansion differences of multilayer materials.

Description

Technical Field

[0001] The present invention relates to the technical field of injection molding process control, and in particular to a multi-layer composite material intelligent mold vision platform system and a manufacturing method thereof. Background Art

[0002] With the growing demand for lightweight materials, multi-layer composite structures (such as honeycomb materials with a foam core layer and a dense surface layer) are increasingly used in the automotive, aerospace and other fields. Traditional mold manufacturing of such products faces the following technical bottlenecks:

[0003] Unstable interlayer bonding quality: Due to differences in thermal expansion coefficients between the layers and inadequate matching of process parameters, defects such as delamination and bubbles are prone to occur. Furthermore, while most current injection molds can achieve alternating injection, they rely on fixed temperature gradient settings and cannot dynamically compensate for material shrinkage, resulting in large fluctuations in interlayer shear strength.

[0004] Inefficient quality inspection: Existing technologies often rely on manual spot checks or offline testing, which cannot correlate defects with process parameters in real time. Traditional methods have a high rate of missed detection of delamination defects, and detection time accounts for a large proportion of the production cycle.

[0005] To this end, a systematic solution that integrates intelligent sensing, real-time quality inspection and dynamic control is urgently needed to improve the manufacturing efficiency and quality consistency of layered composite materials. Summary of the Invention

[0006] The purpose of the present invention is to provide a multi-layer composite material intelligent mold vision platform system and a manufacturing method thereof to solve the problems raised in the background technology.

[0007] To achieve the above objectives, the present invention provides the following technical solutions: a multi-layer composite material intelligent mold visual platform system, the system comprising:

[0008] Modular layered mold, each layer is equipped with an independent temperature control unit and electromagnetic compensation ejector;

[0009] Multi-physics sensor module, integrating temperature, pressure and vibration sensors, to monitor process parameters in real time during mold closing, injection molding and cooling stages;

[0010] Visual quality inspection module, including a line array camera and laser displacement sensor, for online detection of interlayer defects and dimensional tolerances;

[0011] The control platform dynamically optimizes process parameters based on sensor and vision data, and interacts with external management system data.

[0012] The multi-layer composite material intelligent mold vision platform system described in the present invention has a stroke accuracy of the electromagnetic compensation ejector of ±5 μm, a response time of ≤10 ms, and an interlayer contact pressure deviation of less than 3% regulated by a PID algorithm.

[0013] The multi-layer composite material intelligent mold vision platform system of the present invention, wherein the multi-physics field sensor module includes:

[0014] Distributed FBG fiber grating sensors are arranged on each layer of the mold, with a temperature monitoring accuracy of ±0.2°C;

[0015] Piezoelectric film sensor array, with a range of 0-50 MPa, generates a pressure distribution thermogram;

[0016] Piezoelectric ceramic driver, output frequency 5~50Hz mechanical vibration.

[0017] In the multi-layer composite material intelligent mold vision platform system described in the present invention, the visual quality inspection module adopts the improved YOLOX-s algorithm.

[0018] In addition, the present invention also provides a method for manufacturing a multi-layer composite material based on a multi-layer composite material intelligent mold visual platform system, the method comprising the following steps:

[0019] Step S1: setting the layered mold temperature gradient and initial process parameters;

[0020] Step S2: Dynamically adjust the gap between layers through electromagnetic compensation pins during the mold closing stage;

[0021] Step S3: Apply vibration and pressure holding during the injection molding phase, with a frequency of 20 Hz and an amplitude of 100 μm;

[0022] Step S4: After the mold is opened, it is inspected online through the visual quality inspection module, and the defect data is fed back to the control platform in real time.

[0023] In the method for manufacturing multi-layer composite materials based on the multi-layer composite material intelligent mold vision platform system described in the present invention, in step S3, the duration of vibration pressure holding is dynamically adjusted according to the rheological properties of the material, and the adjustment range is 10-30s.

[0024] In the method for manufacturing multi-layer composite materials based on the multi-layer composite material intelligent mold vision platform system described in the present invention, if a delamination defect is detected in step S4, the control platform automatically increases the holding time by 0.3-0.8s and increases the mold temperature gradient by 5-10°C.

[0025] In the method for manufacturing multi-layer composite materials based on the multi-layer composite material intelligent mold visual platform system of the present invention, the specific process of setting the layered mold temperature gradient in step S1 includes:

[0026] The initial temperature gradient ΔT is calculated based on the difference in thermal expansion coefficient of the materials = α × E × h / (1-V 2 ), where α is the material expansion coefficient, E is the elastic modulus, h is the layer thickness, and V is the Poisson's ratio;

[0027] The outer layer mold temperature is set to 180-220℃, and the core layer mold temperature is reduced by 20-50℃;

[0028] The temperature deviation is calibrated in real time to ±0.5°C using distributed FBG fiber grating sensors.

[0029] In the method for manufacturing multi-layer composite materials based on the multi-layer composite material intelligent mold vision platform system of the present invention, the control logic of the vibration pressure maintenance in step S3 is:

[0030] When the inter-layer pressure difference is detected to be ≥5MPa, the trigger vibration frequency is increased from the baseline value of 20Hz to 25-30Hz;

[0031] The amplitude is dynamically adjusted according to the material viscosity. The calculation formula is: A=μ×V / (σ×t), where μ is the melt viscosity, V is the injection volume, σ is the interlayer contact stress, t is the holding time, and the amplitude range is 80-150μm.

[0032] In the method for manufacturing multi-layer composite materials based on the multi-layer composite material intelligent mold vision platform system of the present invention, the feedback in step S4 includes:

[0033] To address the collapse defects of the honeycomb structure, the mold electromagnetic compensation ejector pressure is adjusted to increase by 10% to 15%;

[0034] The process parameters of the next cycle are predicted based on the LSTM model. The output variables include holding time ±0.3s, vibration frequency ±5Hz, and mold temperature gradient ±5℃.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] It achieves dynamic compensation of inter-layer pressure and temperature zone control, solving the problem of traditional molds being unable to adapt to deformation caused by thermal expansion differences in multi-layer materials. It also avoids the drawbacks of existing technologies that use manual sampling or offline testing, resulting in the inability to correlate defects with process parameters in real time. The missed detection rate of delamination defects is further improved, and the proportion of detection time in the production cycle is greatly reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0038] Figure 1 The figure is a flow chart of the process steps of the present invention. DETAILED DESCRIPTION

[0039] The terms "first," "second," "third," and "fourth," etc., in the specification, claims, and accompanying drawings of the present invention are used to distinguish between different items, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements, but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0040] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0041] "Multiple" refers to two or more. "And / or" describes the relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, or B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0042] Moreover, the terms "up, down, left, right, upper end, lower end, longitudinal" and the like indicating directions are all based on the posture and position of the device or apparatus described in this solution during normal use.

[0043] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the following will be a clear and complete description of the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work shall fall within the scope of protection of the present invention.

[0044] This embodiment discloses a multi-layer composite material intelligent mold vision platform system, which includes:

[0045] Modular layered mold, each layer is equipped with an independent temperature control unit and electromagnetic compensation ejector;

[0046] Multi-physics sensor module, integrating temperature, pressure and vibration sensors, to monitor process parameters in real time during mold closing, injection molding and cooling stages;

[0047] Visual quality inspection module, including a line array camera and laser displacement sensor, for online detection of interlayer defects and dimensional tolerances;

[0048] The control platform dynamically optimizes process parameters based on sensor and vision data, and interacts with external management system data.

[0049] Through the attraction of the present invention, dynamic compensation of interlayer pressure and temperature zoning control can be achieved, solving the problem that traditional molds cannot adapt to deformation caused by thermal expansion differences of multi-layer materials; it can also avoid the disadvantages of existing technologies that use manual sampling or offline detection, which makes it impossible to correlate defects with process parameters in real time, further improve the missed detection rate of delamination defects, and greatly reduce the proportion of detection time in the production cycle.

[0050] In this embodiment, the stroke accuracy of the electromagnetic compensation ejector is ±5μm, and the response time is ≤10ms. The PID algorithm is used to adjust the interlayer contact pressure deviation to less than 3% to reduce the interlayer contact pressure fluctuation, thereby avoiding the uneven pressure problem caused by the response delay of the traditional mechanical ejector.

[0051] In this embodiment, the multi-physics field sensor module includes:

[0052] Distributed FBG fiber grating sensors are arranged on each layer of the mold, with a temperature monitoring accuracy of ±0.2°C;

[0053] Piezoelectric film sensor array, with a range of 0-50 MPa, generates a pressure distribution thermogram;

[0054] Piezoelectric ceramic driver, output frequency 5~50Hz mechanical vibration;

[0055] By establishing a three-parameter coupling model of pressure, temperature and vibration, the process controllability is further improved, avoiding the problem that single-parameter control cannot cope with the nonlinear rheological characteristics of the material.

[0056] In this embodiment, the visual quality inspection module adopts the improved YOLOX-s algorithm to improve the accuracy of defect classification and eliminate the problem of high missed detection rate in manual sampling.

[0057] Example 2

[0058] This embodiment is basically the same as the embodiment, and the similarities are not repeated here. The difference is that a method for manufacturing a multilayer composite material based on the system of embodiment 1 is also provided. Figure 1 As shown, the method includes the following steps:

[0059] Step S1: setting the layered mold temperature gradient and initial process parameters;

[0060] Step S2: Dynamically adjust the gap between layers through electromagnetic compensation pins during the mold closing stage;

[0061] Step S3: During the injection molding phase, vibration holding is applied with a frequency of 20 Hz and an amplitude of 100 μm. Vibration holding can further increase the interlayer molecular diffusion coefficient, solving the problem of weak interface bonding caused by insufficient penetration depth of traditional static holding.

[0062] Step S4: After the mold is opened, it is inspected online through the visual quality inspection module, and the defect data is fed back to the control platform in real time.

[0063] In this embodiment, in step S3, the duration of the vibration holding pressure is dynamically adjusted according to the rheological properties of the material, and the adjustment range is 10-30s, so as to automatically match the amplitude (80-150μm adaptive) for materials with different viscosities and avoid fiber orientation disorder caused by universal parameters.

[0064] In this embodiment, in step S4, if a delamination defect is detected, the control platform automatically increases the holding time by 0.3-0.8s and increases the mold temperature gradient by 5-10°C to improve the system feedback response time and reduce the callback fluctuation of traditional PID control.

[0065] In this embodiment, the specific process of setting the temperature gradient of the layered mold in step S1 includes:

[0066] The initial temperature gradient ΔT is calculated based on the difference in thermal expansion coefficient of the materials = α × E × h / (1-V 2 ), where α is the material expansion coefficient, E is the elastic modulus, h is the layer thickness, and V is the Poisson's ratio;

[0067] The outer layer mold temperature is set to 180-220℃, and the core layer mold temperature is reduced by 20-50℃;

[0068] The temperature deviation is calibrated to ±0.5°C in real time through distributed FBG fiber grating sensors;

[0069] This step can reduce the thermal stress deformation and ensure the uniformity of cooling shrinkage of anisotropic materials.

[0070] In this embodiment, the control logic of the vibration pressure maintenance in step S3 is:

[0071] When the inter-layer pressure difference is detected to be ≥5MPa, the trigger vibration frequency is increased from the baseline value of 20Hz to 25-30Hz;

[0072] The amplitude is dynamically adjusted according to the material viscosity. The calculation formula is: A=μ×V / (σ×t), where μ is the melt viscosity, V is the injection volume, σ is the interlayer contact stress, and t is the holding time. The amplitude range is 80-150μm.

[0073] Through the above control logic, the stability of the melt front flow velocity can be improved and the jet flow phenomenon during the injection molding process can be reduced.

[0074] In this embodiment, the feedback in step S4 includes:

[0075] To address the collapse defects of the honeycomb structure, the mold electromagnetic compensation ejector pressure is adjusted to increase by 10% to 15%;

[0076] The process parameters of the next cycle are predicted based on the LSTM model. The output variables include holding time ±0.3s, vibration frequency ±5Hz, and mold temperature gradient ±5℃.

[0077] It should be understood that those skilled in the art can make improvements or changes based on the above description, and all such improvements and changes should fall within the scope of protection of the appended claims of the present invention.

Claims

1. A multi-layer composite material intelligent mold visual platform system, characterized in that: The system includes: Modular layered mold, each layer is equipped with an independent temperature control unit and electromagnetic compensation ejector; Multi-physics sensor module, integrating temperature, pressure and vibration sensors, to monitor process parameters in real time during mold closing, injection molding and cooling stages; Visual quality inspection module, including a line array camera and laser displacement sensor, for online detection of interlayer defects and dimensional tolerances; The control platform dynamically optimizes process parameters based on sensor and vision data, and interacts with external management system data.

2. The multi-layer composite material intelligent mold visual platform system according to claim 1 is characterized in that: The stroke accuracy of the electromagnetic compensation ejector is ±5μm, the response time is ≤10ms, and the interlayer contact pressure deviation is adjusted to be less than 3% through the PID algorithm.

3. The multi-layer composite material intelligent mold visual platform system according to claim 2 is characterized in that: The multi-physics sensor module includes: Distributed FBG fiber grating sensors are arranged on each layer of the mold, with a temperature monitoring accuracy of ±0.2°C; Piezoelectric film sensor array, with a range of 0-50 MPa, generates a pressure distribution thermogram; Piezoelectric ceramic driver, output frequency 5~50Hz mechanical vibration.

4. The multi-layer composite material intelligent mold visual platform system according to claim 1, characterized in that: The visual quality inspection module adopts the improved YOLOX-s algorithm.

5. A method for manufacturing multi-layer composite materials based on a multi-layer composite material intelligent mold vision platform system, the multi-layer composite material intelligent mold vision platform system according to any one of claims 1-4, characterized in that: include: Step S1: setting the layered mold temperature gradient and initial process parameters; Step S2: Dynamically adjust the gap between layers through electromagnetic compensation pins during the mold closing stage; Step S3: Apply vibration and pressure holding during the injection molding phase, with a frequency of 20 Hz and an amplitude of 100 μm; Step S4: After the mold is opened, it is inspected online through the visual quality inspection module, and the defect data is fed back to the control platform in real time.

6. The method for manufacturing multi-layer composite materials based on the multi-layer composite material intelligent mold visual platform system according to claim 5, characterized in that: In step S3, the duration of the vibration pressure holding is dynamically adjusted according to the rheological properties of the material, and the adjustment range is 10-30s.

7. The method for manufacturing multi-layer composite materials based on the multi-layer composite material intelligent mold visual platform system according to claim 6, characterized in that: In step S4, if a delamination defect is detected, the control platform automatically increases the holding time by 0.3-0.8s and increases the mold temperature gradient by 5-10°C.

8. The method for manufacturing multi-layer composite materials based on the multi-layer composite material intelligent mold visual platform system according to claim 5, characterized in that: The specific process of setting the layered mold temperature gradient in step S1 includes: The initial temperature gradient ΔT is calculated based on the difference in thermal expansion coefficient of the materials = α × E × h / (1-V 2 ), where α is the material expansion coefficient, E is the elastic modulus, h is the layer thickness, and V is the Poisson's ratio; The outer layer mold temperature is set to 180-220℃, and the core layer mold temperature is reduced by 20-50℃; The temperature deviation is calibrated in real time to ±0.5°C using distributed FBG fiber grating sensors.

9. The method for manufacturing multi-layer composite materials based on the multi-layer composite material intelligent mold visual platform system according to claim 8, characterized in that: The control logic of the vibration pressure maintenance in step S3 is: When the inter-layer pressure difference is detected to be ≥5MPa, the trigger vibration frequency is increased from the baseline value of 20Hz to 25-30Hz; The amplitude is dynamically adjusted according to the material viscosity. The calculation formula is: A=μ×V / (σ×t), where μ is the melt viscosity, V is the injection volume, σ is the interlayer contact stress, t is the holding time, and the amplitude range is 80-150μm.

10. The method for manufacturing multi-layer composite materials based on the multi-layer composite material intelligent mold visual platform system according to claim 9, characterized in that: The feedback in step S4 includes: To address the collapse defects of the honeycomb structure, the mold electromagnetic compensation ejector pressure is adjusted to increase by 10% to 15%; The process parameters of the next cycle are predicted based on the LSTM model. The output variables include holding time ±0.3s, vibration frequency ±5Hz, and mold temperature gradient ±5℃.

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