Automobile lightweight component manufacturing process real-time monitoring and regulation method

Abstract

The application relates to the field of mechanical engineering and intelligent manufacturing, and discloses a real-time monitoring and regulation method for a manufacturing process of a light-weight automobile part. The method realizes real-time acquisition of a three-dimensional strain field of a resin flow front by embedding a distributed fiber Bragg grating sensing array in a mold; combines a multi-scale pore generation dynamics model to realize online inversion of an un-infiltrated area and pore distribution; and adaptively regulates a pressure gradient of a hot press and a mold temperature field, and dynamically corrects a flow path. The system comprises sensing embedding, strain demodulation, pore inversion, regulation instruction generation and multi-zone execution modules. The application realizes closed-loop accurate control of a porosity of less than 0.5%, and significantly improves the mechanical performance consistency and reliability of the part.

Description

Technical Field

[0001] This invention belongs to the interdisciplinary field of mechanical engineering and intelligent manufacturing, specifically relating to a method for real-time monitoring and control of the manufacturing process of lightweight automotive components. Background Technology

[0002] With the automotive industry's increasing demands for energy conservation, emission reduction, and improved driving range, lightweighting has become a core strategic direction in vehicle design. Carbon fiber reinforced plastics (CFRP), due to its high specific strength, high specific modulus, and excellent corrosion resistance, are widely used in key components such as body structural parts and chassis components. In the manufacturing process of CFRP parts, lamination processes such as resin transfer molding (RTM) or vacuum-assisted resin infusion molding (VARTM) are the mainstream technologies. Their core lies in controlling resin flow to achieve full wetting of the fiber preform, thereby obtaining low-porosity, high-performance composite material products. However, this process highly depends on the precise perception and control of microscale fluid behavior.

[0003] The dynamics of the resin flow front in a complex fiber network directly determine the internal quality of the final product. Due to differences in capillary effects between carbon fiber bundles, the resin wetting rate in different regions is easily unbalanced, leading to defects such as localized dry spots, resin-rich areas, or closed air bubbles, which in turn cause excessive porosity, severely weakening mechanical properties and fatigue life. To ensure molding quality, existing processes typically rely on preset pressure-time curves combined with discretely arranged pressure sensors for process monitoring. However, traditional pressure sensors have limited spatial resolution and are difficult to embed within the fiber preform, failing to capture transient strain and flow field changes at the resin flow front scale of millimeters or even micrometers, resulting in lag or even failure in control.

[0004] Existing research has attempted to introduce indirect monitoring methods such as infrared thermal imaging or dielectric sensing. However, the former is severely affected by mold obstruction, while the latter is highly sensitive to resin systems and has poor versatility. More importantly, current monitoring systems generally lack closed-loop linkage capabilities with actuators, and even if anomalies are identified, they cannot adjust key parameters such as vacuum level, injection pressure, or mold temperature in real time. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention is proposed. Embodiments of this invention provide a method for real-time monitoring and control of the manufacturing process of lightweight automotive components. This method involves embedding a distributed fiber Bragg grating sensor array within the carbon fiber reinforced plastic lamination mold to acquire the dynamic strain field distribution of the resin flow front in three-dimensional space in real time. Combined with a pre-set multi-scale porosity generation kinetic model, online inversion calculations are performed to assess resin impregnation non-uniformity. Based on the inversion results, the resin flow path is dynamically corrected by adaptively adjusting the pressure gradient distribution and temperature field parameters of the hot press, suppressing localized dry spots and pore aggregation caused by fiber bundle capillary effects, thereby achieving closed-loop precise control of the porosity of the molded component.

[0006] The present invention provides a method for real-time monitoring and control of the manufacturing process of lightweight automotive components, comprising:

[0007] After the carbon fiber preform is laid, a distributed fiber Bragg grating sensor array is embedded in an orthogonal grid between the inner surface of the mold cavity and the preform.

[0008] The vacuum-assisted resin transfer molding process is initiated. During the resin injection stage, the center wavelength offset of each grating node is collected in real time by a broadband light source and a high-speed spectral demodulator. Based on the linear coupling relationship between wavelength offset and strain and temperature, the two-dimensional strain gradient field of the resin flow front in the mold plane coordinate system at each time step is decoupled and calculated.

[0009] The two-dimensional strain gradient field is input into a pre-constructed multi-scale pore generation dynamics model. The model is based on Darcy's law and capillary pressure balance equation, and introduces the local permeability tensor and interfacial tension coefficient at the fiber bundle scale. The spatiotemporal evolution equation of resin saturation is solved by discretization using the finite volume method, and the spatial location, area ratio and predicted pore volume fraction of the resin-incompletely wetted area at the current moment are output.

[0010] Based on the deviation between the predicted pore volume fraction and the preset threshold, a pressure gradient control command and a temperature field collaborative correction command are generated. The pressure gradient control command acts on the multi-zone independent hydraulic actuator of the hot press to adjust the amplitude and rise rate of the pressure applied in each zone. The temperature field collaborative correction command acts on the partitioned electric heating elements built into the mold to adjust the set temperature and heating slope of each heating zone.

[0011] During the resin flow and curing stages, the above monitoring, inversion and control cycle is continuously performed until the resin completely fills the cavity and the pore volume fraction is stable below 0.5%.

[0012] Preferably, the grating period of the sensing array is 532 nanometers, the spatial resolution is 5 millimeters, the strain measurement accuracy is one microstrain, and the temperature cross sensitivity, after encapsulation compensation, is less than 0.5 degrees Celsius per microstrain.

[0013] Preferably, after the carbon fiber preform is laid, a distributed fiber Bragg grating sensing array is embedded in an orthogonal grid between the inner surface of the mold cavity and the preform, including:

[0014] The sensing array, consisting of 128 grating units etched on a single optical fiber, is arranged with 64 measuring points along the length and width of the mold, with a spacing of 10 mm between adjacent gratings.

[0015] The sensor array is encapsulated with a polyimide coating, giving it an outer diameter of 125 micrometers and a temperature resistance range of -200 degrees Celsius to 300 degrees Celsius.

[0016] The sensor array is placed in the interface layer between the inner surface of the mold cavity and the carbon fiber preform to ensure that the resin flow front causes local strain changes in the grating area without affecting the resin penetration path.

[0017] Preferably, the vacuum-assisted resin transfer molding process is initiated. During the resin injection stage, the center wavelength offset of each grating node is acquired in real time using a broadband light source and a high-speed spectral demodulator. Based on the linear coupling relationship between wavelength offset and strain and temperature, the two-dimensional strain gradient field of the resin flow front in the mold plane coordinate system at each time step is decoupled and calculated, including:

[0018] Continuous light with a wavelength range of 1520 nm to 1570 nm is emitted through a broadband light source, coupled into the sensing fiber through a circulator, and the reflectance spectrum sequence is acquired by a high-speed spectrometer at a rate of 2000 frames per second.

[0019] The center wavelength of the reflection peak of each grating is located at the sub-picometer level to obtain the center wavelength offset. ;

[0020] Based on fiber Bragg grating sensing equation: ;

[0021] The initial center wavelength, The photoelastic coefficient, The coefficient of thermal expansion is... Thermo-optic coefficient; In response, Temperature change;

[0022] By combining a temperature reference provided by a reference grating or an ambient temperature sensor, the pure strain component is decoupled and separated. ; Represents the two-dimensional spatial coordinates on the mold plane. Represents time;

[0023] Spatial interpolation is performed on the strain values ​​at all measuring points to construct a two-dimensional strain field covering the entire mold plane, and the strain gradient tensor is calculated. To identify the location of the resin flow front.

[0024] Preferably, the two-dimensional strain gradient field is input into a pre-constructed multi-scale pore generation kinetic model. This model is based on Darcy's law and the capillary pressure balance equation, introducing the local permeability tensor and interfacial tension coefficient at the fiber bundle scale. It uses the finite volume method to discretize and solve the spatiotemporal evolution equation of resin saturation, outputting the spatial location, area percentage, and predicted pore volume fraction of the resin-incompletely wetted region at the current moment, including:

[0025] The mass conservation equation As the governing equation, where For local porosity, The density of the resin, Darcy speed;

[0026] Darcy speed is expressed as ,in For local permeability tensor, Resin viscosity, For capillary pressure;

[0027] Capillary pressure From the Young-Laplace equation Confirmed, among which The resin-air interfacial tension. Contact angle, The equivalent radius of the fiber bundle;

[0028] The two-dimensional strain gradient field is converted into a moving boundary condition. The resin flow front propulsion velocity is derived using the strain change rate. The governing equations are then discretized and solved using the finite volume method to obtain the resin saturation. and pore volume fraction .

[0029] Preferably, the local permeability tensor K is obtained by reconstructing the three-dimensional microstructure of the carbon fiber preform using offline micro-CT scanning, and by simulating the resin flow in the structure using the lattice Boltzmann method to calibrate the anisotropic permeability components. .

[0030] Preferably, based on the deviation between the predicted pore volume fraction and a preset threshold, a pressure gradient control command and a temperature field collaborative correction command are generated, including:

[0031] Set a preset pore volume fraction threshold The tolerance is 0.5%. It is 0.1%;

[0032] When the maximum local pore volume fraction Then, construct an inverse optimization problem, with the objective function being... The constraints include a maximum output pressure of 30 MPa for the hot press, a response delay of no more than 50 milliseconds for the hydraulic cylinder, and a maximum local pressure gradient of 5 MPa per centimeter for the strength of the mold structure.

[0033] Solve the inverse optimization problem to obtain the target pressure of 16 independent hydraulic actuators. The target temperature of the 16-group zoned electric heating elements , The range is from 1 to 16. The range is from 1 to 16;

[0034] The optimized result Mapped to spatial continuous pressure gradient control command It is used to accelerate the flow of resin to the low saturation region.

[0035] Preferably, the generation of the temperature field collaborative correction command includes:

[0036] Based on the resin viscosity-temperature index relationship ,in The initial grease viscosity, The activation energy of the resin. The gas constant is Absolute temperature The absolute temperature is The resin viscosity at that time;

[0037] Calculate the local temperature correction amount based on the required viscosity adjustment. To reduce local temperature and increase viscosity to slow down excessively fast flow, or to increase temperature and decrease viscosity to promote resin filling of dry spot areas;

[0038] Will The mapping is to the temperature control command of 16-group zoned electric heating elements.

[0039] Preferably, the above-mentioned monitoring, inversion, and control cycle is continuously performed during the resin flow and curing stages until the resin completely fills the cavity and the pore volume fraction stabilizes below 0.5%, including:

[0040] After the resin injection is completed, the curing stage begins, and the residual strain caused by curing shrinkage at each point is monitored by a distributed fiber Bragg grating sensor array.

[0041] The strain relaxation rate of the entire region is calculated and defined as the absolute value of the strain change per unit time.

[0042] When the strain change rate is less than 5 microstrains per minute, curing is considered complete, and the control cycle is terminated.

[0043] Preferably, the monitoring, inversion and control cycle operates at a frequency of 2 Hz per second, and the control command update cycle is 500 milliseconds.

[0044] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0045] 1. This invention achieves full-field, real-time, and interference-free sensing of microfluidic dynamics at the resin flow front by integrating a high spatial resolution distributed fiber Bragg grating sensing array inside the mold, overcoming the technical limitation of traditional point pressure sensors that cannot capture spatially uneven wetting phenomena.

[0046] 2. The constructed multi-scale pore formation kinetic model integrates macroscopic Darcy flow and microscopic capillary effects, which can accurately invert the unwetted resin area and pore formation trend. On this basis, by adaptively generating and executing the coordinated control commands of pressure gradient and temperature field, the resin flow path is actively corrected, suppressing the formation of dry spots and pores from the source, so that the porosity of the final molded part is stably controlled below 0.5%, improving the mechanical property consistency and structural reliability of carbon fiber reinforced plastic parts, and meeting the stringent quality requirements of automotive lightweighting for high-performance composite material components. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of the overall technical solution architecture of the real-time monitoring and control method for the manufacturing process of lightweight automotive components proposed in this invention;

[0048] Figure 2 This is a schematic diagram of the core principle framework of online inversion of multi-scale pore generation dynamics in this invention;

[0049] Figure 3 This is a flowchart illustrating the logic flow of real-time demodulation of the dynamic strain field at the resin flow front in this invention.

[0050] Figure 4 This is a flowchart illustrating the logical flow of the adaptive pressure-temperature coordinated control command generation in this invention.

[0051] Figure 5 This is a schematic diagram of the multi-level interaction relationship and data flow between the distributed fiber Bragg grating sensing embedding and the multi-zone hydraulic-electrothermal actuation control in this invention;

[0052] Figure 6 This is a diagram illustrating the closed-loop monitoring and control stages and information feedback framework of the entire process from resin injection to curing in this invention. Detailed Implementation

[0053] Please refer to Figures 1 to 6 In the process of carbon fiber reinforced plastic lamination, the resin flow front experiences uneven wetting due to the capillary effect of fiber bundles, leading to excessive porosity. Existing pressure sensors can only acquire pressure values ​​at local points, failing to capture the microfluidic dynamics of resin flow in three-dimensional space, making it difficult to effectively warn and intervene in dry spots and pore aggregation. To address this technical problem, this embodiment provides a real-time monitoring and control method for the manufacturing process of lightweight automotive components. This method embeds a distributed fiber Bragg grating sensor array inside the mold to sense changes in the strain field caused by resin flow in real time; combines this with a preset multi-scale pore generation dynamics model to invert the resin wetting state online; and adaptively adjusts the pressure gradient distribution of the hot press and the mold temperature field based on the inversion results to achieve closed-loop precise control of porosity.

[0054] The method includes the following steps:

[0055] S1. After the carbon fiber preform is laid, a distributed fiber Bragg grating sensor array is embedded in an orthogonal grid between the inner surface of the mold cavity and the preform. The grating period of the sensor array is 532 nanometers, the spatial resolution is 5 millimeters, the strain measurement accuracy is one microstrain, and the temperature cross sensitivity is less than 0.5 degrees Celsius per microstrain after encapsulation compensation.

[0056] Specifically, the distributed fiber Bragg grating sensing array consists of 128 grating units etched onto a single optical fiber, with an adjacent grating spacing of 10 mm. Sixty-four measuring points are arranged along both the length and width of the mold, forming a two-dimensional sensing network covering the entire molding area. This sensing array is encapsulated with a polyimide coating, has an outer diameter of 125 micrometers, and a temperature resistance range of -200°C to 300°C. It withstands shear stress during resin injection without fracture or signal attenuation. The sensing array is positioned at the interface layer between the inner surface of the mold cavity and the carbon fiber preform, ensuring that the resin flow front causes localized strain changes in the grating region without affecting the structural integrity of the preform or the resin penetration path.

[0057] The grating period is set to 532 nm, placing the central reflection wavelength near 1550 nm, within the effective output range of the broadband light source and matching the detection window of the high-speed spectrometer demodulator. The spatial resolution of 5 mm is determined by the spacing between adjacent effective measurement points, and can be further improved to 2.5 mm through interpolation algorithms, meeting the requirements for identifying microscale inhomogeneities at the resin flow front. Strain measurement accuracy—specifically, microstrain—is achieved through high signal-to-noise ratio spectral demodulation and a temperature cross-sensitivity compensation algorithm. The temperature cross-sensitivity is suppressed by matching the thermal expansion coefficients of the dual-grating differential structure or the encapsulation material, ensuring that the strain decoupling error is less than 0.5 degrees Celsius per microstrain.

[0058] S2. Start the vacuum-assisted resin transfer molding process. During the resin injection stage, the center wavelength offset of each grating node is collected in real time by a broadband light source and a high-speed spectral demodulator. Based on the linear coupling relationship between wavelength offset and strain and temperature, the two-dimensional strain gradient field of the resin flow front in the mold plane coordinate system at each time step is decoupled and calculated.

[0059] Specifically, a broadband light source emits continuous light with a wavelength range of 1520 nm to 1570 nm, which is coupled into the sensing fiber via a circulator. Each grating unit reflects a specific wavelength of light signal, and the reflected light returns to the high-speed spectrometer via the same circulator. The high-speed spectrometer acquires the reflection spectrum sequence at a sampling rate of 2000 frames per second, with each frame containing reflection peak information from 128 gratings. Using a peak tracking algorithm, the center wavelength of the reflection peak of each grating is located at the sub-picometer level to obtain the center wavelength offset. According to the basic sensing equation of a fiber Bragg grating, the center wavelength shift is related to strain. and temperature change Satisfies a linear relationship:

[0060] ;

[0061] in The initial center wavelength, The photoelastic coefficient, The coefficient of thermal expansion is... The thermo-optic coefficient is used. Through a pre-calibrated temperature-strain cross-sensitivity matrix, combined with a temperature reference provided by a reference grating or ambient temperature sensor, the thermo-optic coefficient is determined. Decoupling is performed to separate the pure strain components. Subsequently, spatial interpolation was performed on the strain values ​​at all measuring points to construct a two-dimensional strain field covering the entire mold plane. . Represents the two-dimensional spatial coordinates on the mold plane. Representing time. Further calculation of the strain gradient tensor. The principal strain direction and amplitude are extracted to identify the location of the resin flow front—this location corresponds to the region of abrupt strain gradient change, i.e., the transition zone where the strain rapidly increases from 0 to a positive value. The time step is set to 0.5 milliseconds to ensure aliasing-free sampling of the front dynamics at resin flow velocities up to 10 millimeters per second.

[0062] S3. Input the two-dimensional strain gradient field into the pre-constructed multi-scale pore generation dynamics model. The model is based on Darcy's law and capillary pressure balance equation, introduces the local permeability tensor and interfacial tension coefficient at the fiber bundle scale, and solves the spatiotemporal evolution equation of resin saturation by discretization using the finite volume method, outputting the spatial location, area ratio and predicted pore volume fraction of the resin-incompletely wetted area at the current moment.

[0063] The governing equation of the multi-scale porosity formation kinetics model is the mass conservation equation:

[0064] ;

[0065] in For local porosity, The density of the resin, This is Darcy's velocity. Darcy's velocity is given by the generalized Darcy's law:

[0066] ;

[0067] For local permeability tensor, Resin viscosity, This refers to capillary pressure. Determined by the Young-Laplace equation:

[0068] ;

[0069] in The resin-air interfacial tension. Contact angle, Let K be the equivalent radius of the fiber bundle. The local permeability tensor K was used to reconstruct the three-dimensional microstructure of the carbon fiber preform using offline micro-CT scanning, and the resin flow within the structure was simulated using the lattice Boltzmann method. The anisotropic permeability components were then calibrated. Its value is dynamically adjusted according to changes in local fiber volume fraction and orientation. The model's computational domain is consistent with the mold geometry, with a mesh size of 5 mm, matching the spatial resolution of the sensor array. Boundary conditions are derived from the strain gradient field output in step S2: the resin flow front position is used as the moving boundary, and its propulsion velocity is derived from the strain change rate; the inlet pressure is set by the measured pressure at the injection port; the outlet is a vacuum boundary with a pressure of 0. The finite volume method is used to discretize the governing equations, with a time step synchronized with sensor sampling at 0.5 ms. The resin saturation is obtained through iterative solution. Distribution, defining areas with resin saturation less than 0.95 as incompletely wetted areas. Pore volume fraction. From saturation and local porosity Relationship established: The model output includes the set of spatial coordinates of the uninfiltrated area and the percentage of the total area. , ( (total area of ​​the entire study region) and maximum local pore volume fraction .

[0070] S4. Based on the deviation between the predicted pore volume fraction and the preset threshold, a pressure gradient control command and a temperature field collaborative correction command are generated. The pressure gradient control command acts on the multi-zone independent hydraulic actuator of the hot press to adjust the amplitude and rise rate of the pressure applied in each zone. The temperature field collaborative correction command acts on the partitioned electric heating elements built into the mold to adjust the set temperature and heating slope of each heating zone.

[0071] Preset pore volume fraction threshold The tolerance is 0.5%. It is 0.1%. When the model output is This triggers the control mechanism. The control command generation is based on solving an inverse optimization problem: the objective function is to minimize the integral of the squared error between the pore volume fraction and the threshold, i.e.:

[0072] ;

[0073] The constraints include a maximum output pressure of 30 MPa for the hot press hydraulic system, a response delay of no more than 50 milliseconds for each hydraulic cylinder, and a maximum local pressure gradient of 5 MPa per centimeter limited by the strength of the mold structure. The optimization variable is the target pressure of each hydraulic actuator. With the target temperature of each electric heating element ,in From 1 to 16, Numbered from 1 to 16, corresponding to 16 independent control zones. Spatial continuous pressure gradient control command. By optimizing the results Obtained by mapping to a spatial continuum field, used to accelerate resin flow towards low saturation regions. Temperature correction amount. Determined based on the resin viscosity-temperature index relationship:

[0074] ;

[0075] The initial resin viscosity, The activation energy of the resin. The gas constant is Absolute temperature The absolute temperature is The resin viscosity at the time of application and the desired viscosity. Lowering the local temperature increases viscosity and slows down excessively fast flow; raising the temperature decreases viscosity and promotes resin filling of dry spot areas. Temperature correction amount. The required viscosity adjustment is obtained through table lookup or real-time calculation. Control commands are updated at a frequency of 2 Hz and transmitted to the actuator via industrial Ethernet.

[0076] The lookup table refers to pre-establishing a correspondence table between "required viscosity adjustment and temperature correction" by measuring the viscosity data of the target resin system at different temperatures through offline experiments (including matching results of known parameters such as resin viscosity, activation energy, and gas constant). During actual control, after determining the required viscosity adjustment based on the current pore inversion results, the corresponding temperature correction is directly retrieved from the pre-stored table, eliminating the need for real-time calculations and resulting in a fast response time.

[0077] Real-time calculation refers to dynamically deriving the required viscosity adjustment based on the viscosity-temperature index relationship of the resin, combined with the currently monitored pore volume fraction deviation and the real-time state of the resin (such as current viscosity and temperature), and then calculating the corresponding temperature correction in reverse. This method does not rely on pre-stored data, can flexibly adapt to changes in the real-time operating conditions of the resin, and has higher accuracy.

[0078] S5. Continue to perform the above monitoring, inversion and control cycle during the resin flow and curing stage until the resin completely fills the cavity and the pore volume fraction is stable below 0.5%.

[0079] After resin injection, the curing stage begins. At this stage, resin flow ceases, but chemical cross-linking causes volume shrinkage, resulting in residual strain. A distributed fiber Bragg grating sensor array continues to monitor strain changes at various points. The strain relaxation rate is defined as the absolute value of the strain change per unit time. When the strain change rate across the entire region is less than 5 microstrains per minute, the resin curing reaction is considered essentially complete, the molecular chain network structure is stable, and no further significant shrinkage occurs. At this point, the control cycle is terminated, the hydraulic and electrothermal actuators are shut down, and the pressure holding and cooling stage begins. Throughout the process, the monitoring-inversion-control cycle operates at a frequency of 2 Hz to ensure closed-loop control of the entire resin flow and curing process. The final molded part, after ultrasonic C-scan inspection, shows uniform porosity distribution with a maximum pore volume fraction of 0.48%, meeting the stringent requirement of less than 0.5% porosity for automotive structural components.

[0080] Corresponding to the above method, this embodiment also discloses a real-time monitoring and control system for the manufacturing process of lightweight automotive components, which includes a distributed fiber Bragg grating sensing embedding module, a real-time demodulation module for the dynamic strain field of the resin flow front, a multi-scale pore generation dynamics online inversion module, an adaptive pressure-temperature coordinated control command generation module, and a multi-zone hydraulic-electrothermal execution control module.

[0081] A distributed fiber Bragg grating sensing embedding module is used to arrange a sensing array in an orthogonal grid pattern between the carbon fiber preform and the mold cavity. This module includes a fiber deployment robotic arm, a tension controller, and positioning fixtures to ensure that the fiber precisely adheres to the mold surface before preform placement, without wrinkles or gaps. The sensing array integrates 128 gratings from a single fiber, with 64 measuring points along the length and width of the mold, covering an area of ​​over 648 square millimeters. The fiber is encapsulated in polyimide, with an outer diameter of 125 micrometers, and can withstand the shear forces and high temperatures during resin injection.

[0082] The real-time demodulation module for the dynamic strain field at the resin flow front includes a broadband light source, a circulator, a high-speed spectrometer, and a data processing unit. The broadband light source boasts output power stability better than 0.5% and a wavelength range of 1520 to 1570 nanometers. The high-speed spectrometer achieves a sampling rate of 2000 frames per second and a wavelength resolution of 0.1 picometers. The data processing unit executes a peak tracking algorithm and a temperature-strain decoupling procedure, outputting two-dimensional strain field data in real time with a delay of no more than 1 millisecond.

[0083] A multi-scale pore formation dynamics online inversion module is deployed on an industrial computer, equipped with a multi-core processor and graphics acceleration unit. This module loads a pre-built numerical model, receives strain field data as boundary conditions, and uses the finite volume method to solve for resin saturation and pore volume fraction. Model parameters, including local permeability tensor, interfacial tension, and resin viscosity-temperature relationship, are all calibrated through offline experiments. The inversion results are output to the control command generation module at a frequency of 2 Hz.

[0084] The adaptive pressure-temperature coordinated control command generation module runs an inverse optimization algorithm. The objective function is to minimize the pore volume fraction error, and the constraints cover the physical limits of the equipment. This module outputs 16 pressure commands and 16 temperature commands, corresponding to the hydraulic cylinders of the hot press and the electric heating elements of the mold, respectively. The command update cycle is 500 milliseconds to ensure timely control response.

[0085] The multi-zone hydraulic-electric heating control module includes 16 independent servo hydraulic cylinders and 16 zones of electric heating elements. The hydraulic cylinders have a maximum output pressure of 30 MPa and a position repeatability of ±0.05 mm. The electric heating elements utilize thin-film resistance heating technology, achieving a temperature control accuracy of ±1 degree Celsius and a heating rate of up to 10 degrees Celsius per second. After receiving control commands, the module dynamically adjusts the pressure and temperature of each zone, achieving spatial coordinated control.

[0086] This embodiment achieves closed-loop monitoring and active control of the entire process of resin flow and pore formation during carbon fiber reinforced plastic lamination through the above-described method and system. It solves the technical problems of traditional methods being unable to sense microfluidic dynamics and intervene in the formation of local dry spots, thereby improving the quality consistency and structural reliability of lightweight automotive components.

Claims

1. A method for real-time monitoring and regulation of a manufacturing process of a lightweight component for an automobile, characterized in that, Comprise: After the laying of the carbon fiber preform is completed, a distributed fiber Bragg grating sensing array is embedded between the inner cavity surface of the mold and the preform in a orthogonal grid form; Start the vacuum assisted resin transfer molding process, during the resin injection stage, real-time acquisition of the center wavelength shift of each grating node is carried out by a wide spectrum light source and a high-speed spectrum demodulator, according to the linear coupling relationship between the wavelength shift and the strain and temperature, the two-dimensional strain gradient field of the resin flow front in the mold plane coordinate system at each time step is decoupled and calculated, including: A continuous light with a wavelength range of 1520-1570 nm is emitted by a wide spectrum light source, coupled into the sensing fiber through a circulator, and the reflected spectrum sequence is collected by a high-speed spectrum demodulator at a rate of 2000 frames per second; Sub-pi-micron positioning of the reflection peak center wavelength of each grating to obtain the center wavelength shift ; Based on the fiber Bragg grating sensing equation: ; is the initial center wavelength, is the photoelastic coefficient, is the thermal expansion coefficient, is the thermo-optic coefficient; is the strain, temperature change; Decoupling out pure strain components in combination with a temperature reference provided by a reference grating or an ambient temperature sensor ; representing two-dimensional spatial coordinates on the plane of the mold, representing time; The strain values of all measuring points are spatially interpolated to build a two-dimensional strain field covering the entire mold plane, and the strain gradient tensor is calculated , identify the resin flow front position; The two-dimensional strain gradient field is input into the pre-constructed multi-scale pore generation dynamics model, the model is based on Darcy's law and capillary pressure balance equation, introduces the local permeability tensor and interfacial tension coefficient at the fiber bundle scale, solves the resin saturation spatio-temporal evolution equation by finite volume method, and outputs the spatial position, area ratio and predicted pore volume fraction of the region not completely infiltrated by resin at the current time, including: The mass conservation equation as a control equation, where is the local porosity, is the resin density, is the Darcy velocity; The Darcy velocity is expressed as where is the local permeability tensor, is the resin viscosity, is the capillary pressure; capillary pressure determined from the Young-Laplace equation where is the resin-air interfacial tension, is the contact angle, is the fiber bundle equivalent radius; The two-dimensional strain gradient field is converted into a moving boundary condition, a resin flow front advancing speed is derived with a strain change rate, control equations are discretely solved by using a finite volume method, and resin saturation is obtained and a pore volume fraction ; According to the deviation of the predicted pore volume fraction and the preset threshold, pressure gradient control instructions and temperature field cooperative correction instructions are generated; the pressure gradient control instructions act on the multi-zone independent hydraulic execution unit of the hot press to adjust the amplitude and rising rate of the pressure applied in each region; the temperature field cooperative correction instructions act on the partitioned electric heating sheet built in the mold to adjust the set temperature and heating slope of each heating region; The above monitoring, inversion and control cycle is continuously executed during the resin flow and curing stage until the resin completely fills the cavity and the pore volume fraction is stable below 0.5%.

2. The method of claim 1, wherein the method is characterized by: The grating period of the sensing array is 532 nm, the spatial resolution is 5 mm, the strain measurement accuracy is one micro-strain, and the temperature cross-sensitivity is less than 0.5 degrees Celsius per micro-strain after packaging compensation.

3. The method of claim 2, wherein the method further comprises: After the laying of the carbon fiber preform is completed, a distributed fiber Bragg grating sensing array is embedded between the inner cavity surface of the mold and the preform in a orthogonal grid form, including: A sensing array composed of 128 grating units written on a single optical fiber is arranged along the length and width directions of the mold, with a spacing of 10 mm between adjacent gratings; The sensing array is packaged with a polyimide coating, with an outer diameter of 125 microns and a temperature resistance range of -200 to 300 degrees Celsius; The sensing array is arranged on the interface layer between the inner cavity surface of the mold and the carbon fiber preform, ensuring that the resin flow front causes local strain changes in the grating region without affecting the resin infiltration path.

4. The method of claim 3, wherein the method further comprises: The local permeability tensor K is calibrated by reconstructing the three-dimensional microstructure of the carbon fiber preform through off-line micro-CT scanning and simulating the resin flow in the structure using the lattice Boltzmann method .

5. The method of claim 4, wherein the method further comprises: According to the deviation of the predicted pore volume fraction and the preset threshold, pressure gradient control instructions and temperature field cooperative correction instructions are generated, including: Setting a preset pore volume fraction threshold is 0.5%, allowable deviation is 0.1%; When the maximum local pore volume fraction An inverse optimization problem is constructed with an objective function , and constraints including a maximum output pressure of the hot press of 30 MPa, a hydraulic cylinder response delay of no more than 50 milliseconds, and a maximum local pressure gradient of 5 MPa per centimeter for the mold structure strength limitation. solving the inverse optimization problem to obtain target pressures of 16 independent hydraulic actuation units target temperatures of 16 groups of partitioned electric heating sheets , is 1 to 16, is 1 to 16; The optimized mapping to spatially continuous pressure gradient regulation instructions for accelerating the resin flow to the low saturation region.

6. The method of claim 5, wherein the method further comprises: The generation of the temperature field cooperative correction instructions includes: Based on resin viscosity-temperature index relationship wherein is the initial resin viscosity, is the resin activation energy, is the gas constant, is the absolute temperature, is the absolute temperature is the resin viscosity at time; Adjust the local temperature correction amount according to the required viscosity adjustment amount To reduce the local temperature to slow down the too fast flow caused by viscosity increase, or to increase the temperature to promote the resin filling the dry area by reducing the viscosity. The temperature regulation instructions are mapped as 16 groups of partitioned electric heating sheets. The temperature regulation instructions are mapped as 16 groups of partitioned electric heating sheets.

7. The method of claim 6, wherein the method further comprises: determining a current state of the manufacturing process; and determining a current state of the manufacturing process based on the determined current state of the manufacturing process. The above monitoring, inversion and control cycle is continuously executed during the resin flow and curing stage until the resin completely fills the cavity and the pore volume fraction is stable below 0.5%, including: After the resin injection is completed and enters the curing stage, the residual strain caused by curing shrinkage at each point is continuously monitored by the distributed fiber Bragg grating sensing array; The strain relaxation rate of the entire area is calculated, which is defined as the absolute value of the strain change per unit time; When the strain change rate is lower than 5 micro-strains per minute, it is determined that the curing is completed, and the regulation cycle is terminated.

8. The method of claim 7, wherein the method further comprises: The monitoring, inversion and regulation cycle runs at a frequency of 2 hertz per second, and the regulation instruction update period is 500 milliseconds.

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